BEGIN:VCALENDAR PRODID:-//github.com/ical-org/ical.net//NONSGML ical.net 4.0//EN VERSION:2.0 BEGIN:VTIMEZONE TZID:America/New_York X-LIC-LOCATION:America/New_York BEGIN:STANDARD DTSTART:20241103T020000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST TZOFFSETFROM:-0400 TZOFFSETTO:-0500 END:STANDARD BEGIN:DAYLIGHT DTSTART:20250309T020000 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT TZOFFSETFROM:-0500 TZOFFSETTO:-0400 END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:The Journey lectures are non-technical talks showcasing the ca reer of a data scientist and describes the twists and turns that make a j ourney interesting. The format is 40 minutes of presentation followed by a 20 minutes of Q&A with the audience. The journey lecturer is typically introduced by their trainee. We serve a comfort snack chosen by the Journ ey Lecturer to bring a personal touch to the forum. These lectures serve as professional development resources that are personalized and provides insights into how career decisions happen in real life. This is a unique opportunity to learn about the life and career of your colleague and/or m entor.\n\nAdmission:\nFree\n\nFood:\nSnacks: Speaker's favorite snack (GO RP) will be served.\n\nDetails URL:\nhttps://medicine.yale.edu/event/jour ney-lecture-1/\n DTEND;TZID=America/New_York:20241206T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20241206T120000 GEO:41.303666;-72.932218 LOCATION:Yale School of Public Health (LEPH)\, 109\, 60 College Street\, N ew Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Journey Lecture by Jeffrey Townsend\, PhD UID:14ad653b-572d-4c43-8aa8-6aef093555ef END:VEVENT BEGIN:VEVENT DESCRIPTION:The Office of Academic & Professional Development (OAPD) offer s faculty workshops throughout the academic year (Sept. – June) to suppor t professional and career development. While geared toward assistant prof essors and research rank faculty\, all faculty are welcome to attend. Con tinuing Medical Education (CME) credit is available for those who partici pate.\n\nSpeakers:\nAllen Hsiao\; Gunjan Tiyyagura\n\nAdmission:\nFree\n\ nDetails URL:\nhttps://medicine.yale.edu/event/artificial-intelligence-in -healthcare-the-hype-and-the-hope/\n DTEND;TZID=America/New_York:20250108T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250108T160000 LOCATION:The Office of Academic & Professional Development (OAPD) offers f aculty workshops throughout the academic year (Sept. – June) to support p rofessional and career development. While geared toward assistant profess ors and research rank faculty\, all faculty are welcome to attend. Contin uing Medical Education (CME) credit is available for those who participat e.\, URL: https://yale.zoom.us/meeting/register/tJIoceyorTwsG9Abb7H_UlZuD BK3HQ4KVL7B SEQUENCE:0 STATUS:Confirmed SUMMARY:Artificial Intelligence in Healthcare: The Hype and the Hope UID:3ec84b10-cc85-4704-8613-7397de1a4cf1 END:VEVENT BEGIN:VEVENT DESCRIPTION:Single-cell RNA-seq has revolutionized our understanding of hu man biology\, profiling hundreds of millions of cells across tissues\, di seases\, and experimental systems. However\, unlocking the full potential of this data requires a unified way to measure and compare cell states a cross diverse contexts. In this seminar\, Dr. Jason Vander Heiden will in troduce SCimilarity\, an innovative metric-learning framework that enable s rapid searches across tens of millions of cell profiles to identify tra nscriptionally similar cell states. SCimilarity empowers researchers to u ncover disease mechanisms\, assess drug target safety\, and guide therape utic strategies. Through a case study on fibrotic lung disease\, Dr. Vand er Heiden will demonstrate how SCimilarity identified fibrosis-associated macrophages as a therapeutic target\, paving the way for novel treatment s.\n\nSpeaker:\nJason A. Vander Heiden\, PhD\n\nAdmission:\nFree\n\nFood: \nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/research-in-prog ress-or-rising-star-seminar-vander-heiden/\n DTEND;TZID=America/New_York:20250109T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250109T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/99141783583 SEQUENCE:0 STATUS:Confirmed SUMMARY:Research in Progress | Rising Star Seminar UID:6e83f35c-ace5-430d-94c8-c449d416a703 END:VEVENT BEGIN:VEVENT DESCRIPTION:Dr. Luciano Floridi (Laurea\, Rome La Sapienza\; M.Phil. and P h.D.\, University of Warwick) is the Founding Director of the Digital Eth ics Center and a Professor in the Cognitive Science Program at Yale Unive rsity. A leading figure in contemporary philosophy and the founder of the philosophy of information\, he has written over 300 publications on digi tal ethics\, AI ethics\, and the philosophy of technology. Dr. Floridi’s recent books include The Ethics of Artificial Intelligence(OUP\, 2023) an d The Green and The Blue (Wiley\, 2023). In 2022\, he was knighted as a K night of the Grand Cross OMRI for his contributions to philosophy. The ri se of Generative AI (GenAI) is transforming content creation\, disseminat ion\, and consumption\, challenging traditional notions of authorship and reshaping the relationship between producers and consumers. As we move t oward an AI-driven world\, understanding the implications of this shift i s essential. In this talk\, Dr. Luciano Floridi explores the future of co ntent in the age of GenAI\, analyzing the evolving definition of content\ , the transformations brought about by GenAI systems\, and emerging model s of content production and dissemination. By examining these aspects\, w e can gain valuable insights into the challenges and opportunities that l ie ahead in the realm of content creation and consumption and\, hopefully \, manage them more successfully.\n\nSpeaker:\nLuciano Floridi\n\nAdmissi on:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/even t/bids-monthly-seminar-series-dr-luciano-floridi/\n DTEND;TZID=America/New_York:20250116T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250116T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Cancelled SUMMARY:BIDS Monthly Seminar Series - Dr. Luciano Floridi UID:c9d42e15-753c-4815-9c5c-7fe5d70d83f7 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\,present ongoing AI work\, and disc uss potential collaboration at bi-weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 100 Coll ege St\, 11th Floor (WTI)\, Room 1167 unless stated otherwise We provide a zoom link for those who may not be able to join. Thanks.\n\nAdmission:\ nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/yale-nlpllm-intere st-group-14/\n DTEND;TZID=America/New_York:20250220T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250220T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250220T163000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\,present ongoing AI work\, and disc uss potential collaboration at bi-weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 100 Coll ege St\, 11th Floor (WTI)\, Room 1167 unless stated otherwise We provide a zoom link for those who may not be able to join. Thanks.\n\nAdmission:\ nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/yale-nlpllm-intere st-group-15/\n DTEND;TZID=America/New_York:20250320T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250320T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250320T163000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\,present ongoing AI work\, and disc uss potential collaboration at bi-weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 100 Coll ege St\, 11th Floor (WTI)\, Room 1167 unless stated otherwise We provide a zoom link for those who may not be able to join. Thanks.\n\nAdmission:\ nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/yale-nlpllm-intere st-group-16/\n DTEND;TZID=America/New_York:20250417T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250417T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250417T163000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\,present ongoing AI work\, and disc uss potential collaboration at bi-weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 101 Coll ege St\, 10th Floor unless stated otherwise We provide a zoom link for th ose who may not be able to join. Thanks.\n\nAdmission:\nFree\n\nDetails U RL:\nhttps://medicine.yale.edu/event/yale-nlpllm-interest-group-18/\n DTEND;TZID=America/New_York:20250619T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250619T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250619T163000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\,present ongoing AI work\, and disc uss potential collaboration at bi-weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 101 Coll ege St\, 10th Floor unless stated otherwise We provide a zoom link for th ose who may not be able to join. Thanks.\n\nAdmission:\nFree\n\nDetails U RL:\nhttps://medicine.yale.edu/event/yale-nlpllm-interest-group-20/\n DTEND;TZID=America/New_York:20250821T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250821T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250821T163000 SEQUENCE:0 STATUS:Cancelled SUMMARY:Yale NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\, present ongoing AI work\, and dis cuss potential collaboration at a weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 101 Coll ege St\, 10th Floor unless stated otherwise We provide a zoom link for th ose who may not be able to join. Thanks.\n\nAdmission:\nFree\n\nDetails U RL:\nhttps://medicine.yale.edu/event/yale-nlpllm-interest-group-1/\n DTEND;TZID=America/New_York:20250116T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250116T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250116T163000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\, present ongoing AI work\, and dis cuss potential collaboration at a weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 101 Coll ege St\, 10th Floor unless stated otherwise We provide a zoom link for th ose who may not be able to join. Thanks.\n\nAdmission:\nFree\n\nDetails U RL:\nhttps://medicine.yale.edu/event/yale-nlpllm-interest-group-2/\n DTEND;TZID=America/New_York:20250515T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250515T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250515T163000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\, present ongoing AI work\, and dis cuss potential collaboration at a weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 101 Coll ege St\, 10th Floor unless stated otherwise We provide a zoom link for th ose who may not be able to join. Thanks.\n\nAdmission:\nFree\n\nDetails U RL:\nhttps://medicine.yale.edu/event/yale-nlpllm-interest-group-3/\n DTEND;TZID=America/New_York:20250717T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250717T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RECURRENCE-ID;TZID=America/New_York:20250717T163000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:This is a continuation of our interest group on natural langua ge processing (NLP) across multiple schools at Yale. We will have faculty and students to share research ideas\, present ongoing AI work\, and dis cuss potential collaboration at a weekly meetings. It is open to anyone w ho is interested in NLP/LLM at Yale. It is an in-person event at 101 Coll ege St\, 10th Floor unless stated otherwise We provide a zoom link for th ose who may not be able to join. Thanks.\n\nAdmission:\nFree\n DTEND;TZID=America/New_York:20250116T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250116T163000 EXDATE:20250116T163000 EXDATE:20250515T163000 EXDATE:20250717T163000 EXDATE:20250918T163000 EXDATE:20251016T163000 EXDATE:20251120T163000 EXDATE:20251218T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 RRULE:FREQ=MONTHLY;UNTIL=20250902T035959Z;BYDAY=3TH SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:eb7ea530-8319-4ba5-b72b-3efd61edeed8 END:VEVENT BEGIN:VEVENT DESCRIPTION:The Office of Academic & Professional Development (OAPD) offer s faculty workshops throughout the academic year (Sept. – June) to suppor t professional and career development. While geared toward assistant prof essors and research rank faculty\, all faculty are welcome to attend. Con tinuing Medical Education (CME) credit is available for those who partici pate.\n\nSpeaker:\nLucila Ohno-Machado\n\nAdmission:\nFree\n\nDetails URL :\nhttps://medicine.yale.edu/event/biomedical-informatics-and-data-scienc e-resources-and-opportunities/\n DTEND;TZID=America/New_York:20250122T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250122T160000 LOCATION:The Office of Academic & Professional Development (OAPD) offers f aculty workshops throughout the academic year (Sept. – June) to support p rofessional and career development. While geared toward assistant profess ors and research rank faculty\, all faculty are welcome to attend. Contin uing Medical Education (CME) credit is available for those who participat e.\, URL: https://yale.zoom.us/meeting/register/tJ0rf-GqpjsiH9Q9uYPoOdfJf GUtUU3xWkTH SEQUENCE:0 STATUS:Confirmed SUMMARY:Biomedical Informatics and Data Science: Resources and Opportuniti es UID:ff709e3b-c5bc-44bb-850d-0905460c5bd2 END:VEVENT BEGIN:VEVENT DESCRIPTION:The Yale Data-Intensive Social Science Center (DISSC) and The Yale Office of Research Development (YRD) is inviting you to this informa tional webinar about the NSF National Artificial Intelligence Research Re source (NAIRR) Pilot Program .Thursday\, January 23\, 2025 11 AM - 12 PM RSVP for this event by 1/21/25. Closer to the event date\, you will recei ve a calendar invite with zoom link. This event will be beneficial to any faculty or graduate students interested in learning about resources and opportunities offered in this NSF program.\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/nsf-the-national-artificial-intell igence-research-resource-nairr-informational-webinar/\n DTEND;TZID=America/New_York:20250123T120000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250123T110000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NSF - The National Artificial Intelligence Research Resource (NAIR R) Informational Webinar UID:740cba53-cb7a-4f9e-82d4-8ce9ecc6eabe END:VEVENT BEGIN:VEVENT DESCRIPTION:Join Drs. Lucila Ohno-Machado and Bhramar Mukherjee for the in augural BIS and BIDS joint lunch session! This pilot initiative aims to f oster collaboration and facilitate the exchange of research ideas between the closely connected departments of Biostatistics and Biomedical Inform atics & Data Science. We’re excited to create an informal space for learn ing and discussion over lunch.\n\nSpeakers:\nLucila Ohno-Machado\; Bhrama r Mukherjee\n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps:// medicine.yale.edu/event/bisbids-monthly-seminar-series/\n DTEND;TZID=America/New_York:20250123T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250123T120000 LOCATION:Zoom \, URL: https://yale.zoom.us/j/91434839882 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIS/BIDS Monthly Seminar Series UID:8547ec6d-84d8-4ecd-a3ed-2b820ccf4afe END:VEVENT BEGIN:VEVENT DESCRIPTION:This class provides a high-level overview of the All of Us Res earch Program \, an NIH initiative with data from over 849\,000 participa nts\, including electronic health records\, whole genome sequencing\, Fit bit devices\, surveys\, medications\, laboratory measures\, and more. Thi s class will cover the program's purpose\, data sources\, storage\, creat ing datasets\, and analytic tools available through the Researcher Workbe nch. Participants will also have a chance to create a user account and re gister for data access. This course serves as a prerequisite for future A ll of Us training courses offered by the Cushing / Whitney Medical Librar y. This class will be held in-person at the Cushing / Whitney Medical Lib rary on 1/27/2025 from 1-3pm in room E 28/29. Please bring a laptop and i f you intend to create an All of Us account\, an official government issu ed ID (driver’s license or passport).\n\nSpeaker:\nMaximilian Wegener\n\n Admission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/medical -library-classes-and-events-all-of-us/\n DTEND;TZID=America/New_York:20250127T150000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250127T140000 GEO:41.303333;-72.933741 LOCATION:Harvey Cushing/John Hay Whitney Medical Library \, E 28/29\, 333 Cedar Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Medical Library Classes & Events UID:df560233-05a8-4b64-b8d2-199c9eeaf807 END:VEVENT BEGIN:VEVENT DESCRIPTION:Large language models (LLMs) have been touted as the cure all for what ails medical education - a tireless teaching assistant that can create custom lesson plans at 3 AM\, patiently explain the Krebs cycle fo r the fifth time\, and support Knowles' adult learning theory by fosterin g problem-oriented\, self-motivated knowledge acquisition. However\, they also occasionally spout nonsense with unwavering confidence and lack the emotional intelligence to nurture critical thinking and professional ide ntity formation that only happens in human-to-human connections. In this talk\, Dr. Robert Homer will explore both sides of LLMs' role\, including (hopefully) live demonstrations. Robert Homer\, MD\, PhD\, is a Yale-tra ined clinician educator with extensive expertise in research\, clinical c are\, and medical education. His career has focused on diagnostic and exp erimental lung pathology\, including inflammatory and neoplastic lung dis eases and pulmonary fibrosis. Dr. Homer served as Yale's lead thoracic pa thologist and as Director of Anatomic Pathology at the West Haven VA for nearly two decades. As Director of Medical Education for Pathology\, Dr. Homer co-directs the “Attacks and Defenses” course and explores innovativ e uses of large language models to enhance learning and assessment in med ical education.\n\nSpeaker:\nRobert Homer\n\nAdmission:\nFree\n\nFood:\nL unch\n\nDetails URL:\nhttps://medicine.yale.edu/event/ai-in-medicine-rob- homer/\n DTEND;TZID=America/New_York:20250130T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250130T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:AI in Medicine Seminar Series UID:a5563848-ab70-4f90-8211-7d9b6f6d8a37 END:VEVENT BEGIN:VEVENT DESCRIPTION:This a monthly webinar provided by YNHHS Epic Clinician Builde rs to help clinicians (MDs and APPs) become more efficient and proficient in the use of our Epic electronic health record.\n\nSpeaker:\nRitche Hao \n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/mak e-epic-easier-chart-review-tips-and-a-few-tricks/\n DTEND;TZID=America/New_York:20250206T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250206T121500 LOCATION:Zoom. Passcode: 812090.\, URL: https://ynhh.zoom.us/j/95945390228 ?pwd=bnU0YW5QL1VJVVVCN1BCVkpldkVCZz09 SEQUENCE:0 STATUS:Confirmed SUMMARY:Make Epic Easier - Chart Review: Tips and a Few Tricks UID:86abfce3-ca0c-4de6-a1b2-8b760e850a7a END:VEVENT BEGIN:VEVENT DESCRIPTION:\nSpeaker:\nDaniella Meeker\n\nAdmission:\nFree\n\nDetails URL :\nhttps://medicine.yale.edu/event/using-medical-records/\n DTEND;TZID=America/New_York:20250207T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250207T120000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Using Medical Records UID:3c506045-b59e-4439-81b5-966585e9aefa END:VEVENT BEGIN:VEVENT DESCRIPTION:Session 1 - Eye as the Window into Cardiovascular Diseases & A ging in the Era of Big Data Dr. Ching-Yu Cheng\, a renowned physician-sci entist in ophthalmology and data science from the National University of Singapore. Dr. Cheng will present groundbreaking research on how the reti na\, a biomarker-rich platform\, offers a non-invasive window into system ic health-particularly cardiovascular diseases (CVD) and biological aging . Abstract: The retina offers a unique\, non-invasive view into systemic health\, serving as a biomarker-rich platform for detecting cardiovascula r diseases (CVD) and assessing biological aging. In the era of big data\, advancements in Al have revolutionized our ability to extract clinically meaningful information from retinal images. This talk will explore how A l-driven retinal analysis enables early detection of CVD\, risk stratific ation\, and personalized health assessments. Additionally\, I will discus s emerging research on predicting biological age from retinal features\, offering insights into aging trajectories and disease susceptibility. By integrating Al with large-scale retinal imaging datasets\, we move toward a future where routine eye exams could provide a window into cardiovascu lar and systemic health\, enhancing preventive medicine and precision hea lthcare. Session 2 - Vision and Language Foundation Models in Ophthalmolo gy: Where We Are & Where We're Headed Dr. Yih Chung Tham\, a leading expe rt in big data analytics\, ocular imaging\, and Al applications in ophtha lmology from the National University of Singapore. Dr. Tham will delve in to the transformative role of vision and language foundational models at the forefront of the Al and generative Al revolution\, reshaping not only ophthalmology but also the broader landscape of medical research and pra ctice. Abstract: Vision and language foundational models are at the foref ront of the Al and generative Al revolution\, transforming ophthalmology and beyond. In this talk\, Dr. Tham will explore the rapidly evolving lan dscape of these models\, highlighting key breakthroughs\, challenges\, an d real-world applications. He will discuss the expanding role of multimod al Al in clinical decision-making and medical education\, while outlining the critical next steps for refining and implementing these technologies effectively.\n\nSpeakers:\nChing-Yu Cheng\, MD\, MPH\, PhD\; Yih Chung T ham\, PhD\n\nAdmission:\nFree\n\nFood:\nSnacks\n\nDetails URL:\nhttps://m edicine.yale.edu/event/yale-nlpllm-interest-group-special-seminar/\n DTEND;TZID=America/New_York:20250210T143000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250210T130000 LOCATION:Zoom \, URL: https://yale.zoom.us/j/3555437215 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale NLP/LLM Interest Group UID:3afe6d0e-a899-48c3-85f8-606255502df0 END:VEVENT BEGIN:VEVENT DESCRIPTION:AI has the potential to transform healthcare\, improving diagn ostic accuracy and enabling early disease prediction. However\, when trai ned on electronic health records (EHR) and other observational data\, AI models often inherit biases that impact their generalizability and clinic al decision-making. In this seminar\, Dr. Shalmali Joshi will explore how bias propagates in AI-based diagnostic models—focusing on chest radiogra phs and clinical psychiatry—and discuss strategies to improve model relia bility. She will also highlight ways to extend these frameworks to genera tive AI in medicine. Dr. Joshi is an assistant professor at Columbia Univ ersity\, Department of Biomedical Informatics and director of the reAIM L ab\, specializing in AI and machine learning for healthcare. Her work spa ns deep learning\, reinforcement learning\, causal inference\, and probab ilistic modeling. Previously a Postdoctoral Fellow at Harvard and the Vec tor Institute\, she was recognized as one of MIT-EECS’s Rising Stars in 2 021.\n\nSpeaker:\nShalmali Joshi\, PhD\n\nAdmission:\nFree\n\nFood:\nLunc h\n\nDetails URL:\nhttps://medicine.yale.edu/event/research-in-progress-o r-rising-star-seminar-joshi/\n DTEND;TZID=America/New_York:20250213T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250213T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/99141783583 SEQUENCE:0 STATUS:Confirmed SUMMARY:Research in Progress | Rising Star Seminar UID:0f810ef4-0084-454d-99a9-18657323ac1e END:VEVENT BEGIN:VEVENT DESCRIPTION:Scientists hope to use AI to uncover new insightsfrom existing datasets\, but poor-quality metadata often makes this impossible. Withou t clear\, standardized metadata\, datasets in public repositories remain difficult to interpret and reuse. Tools like the CEDAR Workbench and NIH Hu BMAP’s Metadata Validator help researchers create and standardize high-qu ality metadata\, making data more accessible and usable. These tools also allow scientific communities to encode metadata standards into reusable\ , machine-actionable templates\, enabling consistent data sharing and pav ing the way for AI-driven discoveries. Dr. Mark Musen is a Professor of B iomedical Informatics Research at Stanford Medicine\, where he directs th e Stanford Center for Biomedical Informatics Research. He led the develop ment of Protégé\, the world’s leading ontology platform\, and served as p rincipal investigator for the National Center for Biomedical Ontology and CEDAR. He also chaired the WHO’s Health Informatics and Modeling Group f or ICD-11 and directs the WHO Collaborating Center at Stanford.\n\nSpeake r:\nMark Musen\, MD\, PhD\n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/bids-monthly-seminar-series-dr-mark -musen/\n DTEND;TZID=America/New_York:20250220T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250220T120000 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar Series - Dr. Mark Musen UID:83f6e13b-6c47-460e-9686-a35b9a794303 END:VEVENT BEGIN:VEVENT DESCRIPTION:Join Zoom Meeting https://yale.zoom.us/j/98567940106?pwd=Mocp3 J7eBTq47asGfbBt5H8HbeXv5q.1&from=addon\n\nSpeaker:\nLucila Ohno-Machado\n \nAdmission:\nFree\n\nFood:\nBreakfast\n\nDetails URL:\nhttps://medicine. yale.edu/event/therapeutic-radiology-grand-rounds-tbn-medical-ai-and-oppo rtunities-at-yale/\n DTEND;TZID=America/New_York:20250227T100000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250227T090000 GEO:41.304582;-72.936000 LOCATION:Smilow Cancer Hospital at Yale New Haven\, LL505\, 35 Park Street \, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Therapeutic Radiology Grand Rounds: "Medical AI and Opportunities at Yale" UID:029c03f9-a248-43a9-bcb3-c1026fc9c797 END:VEVENT BEGIN:VEVENT DESCRIPTION:Discover how AI is transforming health care worldwide in a sem inar led by Dr. Uwe Fischer\, an expert in integrating AI into vascular s urgery at Yale School of Medicine. From IBM Watson and Google DeepMind in the U.S. to groundbreaking innovations in China\, the U.K.\, Israel\, an d beyond\, AI is improving diagnostics\, streamlining treatments\, and ad vancing personalized medicine. Dr. Fischer will highlight global efforts i n ethical AI\, data security\, and collaboration to enhance patient outco mes. Dr. Uwe Fischer specializes in vascular surgery at Yale School of Me dicine. With an M.D. and Ph.D. from Johannes Gutenberg University of Main z and advanced AI training from MIT and Harvard\, his work focuses on usi ng AI to improve vascular diagnostics and treatments. He is also dedicate d to mentoring medical students on integrating AI into clinical practice. \n\nSpeaker:\nUwe Fischer\n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/ai-in-medicine-fischer/\n DTEND;TZID=America/New_York:20250227T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250227T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/99141783583 SEQUENCE:0 STATUS:Confirmed SUMMARY:AI in Medicine Student Interest Group Monthly Seminar UID:61655dd6-b03d-4608-be9e-7e0a1f31834a END:VEVENT BEGIN:VEVENT DESCRIPTION:\nSpeakers:\nBrian Williams\; Michael Connolly\n\nAdmission:\n Free\n\nDetails URL:\nhttps://medicine.yale.edu/event/akingmbulatoryoding asier/\n DTEND;TZID=America/New_York:20250306T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250306T121500 LOCATION:Please click the link below to join the webinar:\nhttps://ynhh.zo om.us/j/95945390228?pwd=bnU0YW5QL1VJVVVCN1BCVkpldkVCZz09\nPasscode: 81209 0\, URL: https://ynhh.zoom.us/j/95945390228?pwd=bnU0YW5QL1VJVVVCN1BCVkpld kVCZz09 SEQUENCE:0 STATUS:Confirmed SUMMARY:Making Epic Easier - Tips for the Busy Clinician UID:6760cb62-9125-4e23-88e9-41912ad8e555 END:VEVENT BEGIN:VEVENT DESCRIPTION:OBGYN Grand Rounds by David Coleman\, MD and Lucila Ohno-Macha do\, MD\, MBA\, PhD: "Update on the Yale Center for Clinical Investigatio n" and "Medical AI\, Informatics and Data Science"\n\nSpeakers:\nDavid Co leman\; Lucila Ohno-Machado\n\nAdmission:\nFree\n\nDetails URL:\nhttps:// medicine.yale.edu/event/obgyn-grand-rounds-update-yale-center-clinical-in vestigation-medical-ai-informatics/\n DTEND;TZID=America/New_York:20250313T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250313T160000 LOCATION:URL: https://yale.zoom.us/j/95488075222 SEQUENCE:0 STATUS:Confirmed SUMMARY:OBGYN Grand Rounds: Update on the Yale Center for Clinical Investi gation and Medical AI\, Informatics and Data Science UID:3c14b5e2-2282-4278-82dd-9a06886c2d14 END:VEVENT BEGIN:VEVENT DESCRIPTION:Join Zoom Meeting https://yale.zoom.us/j/98567940106?pwd=Mocp3 J7eBTq47asGfbBt5H8HbeXv5q.1&from=addon\n\nSpeaker:\nJun Deng\n\nAdmission :\nFree\n\nFood:\nLight breakfast\, coffee\, tea\n\nDetails URL:\nhttps:/ /medicine.yale.edu/event/therapeutic-radiology-grand-rounds-ai-and-digita l-twins-for-precision-medicine-opportunities/\n DTEND;TZID=America/New_York:20250320T100000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250320T090000 GEO:41.304582;-72.936000 LOCATION:Smilow Cancer Hospital at Yale New Haven\, LL505\, 35 Park Street \, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Therapeutic Radiology Grand Rounds: "AI and Digital Twins for Prec ision Medicine: Opportunities and Challenges" UID:7015c11a-3366-4910-b534-3698fe268762 END:VEVENT BEGIN:VEVENT DESCRIPTION:Suzanne Bakken\, PhD\, RN\, FAAN\, FACMI\, FIASHI is the Alumn i Professor of Nursing and Professor of Biomedical Informatics at Columbi a University. She also serves as the Executive Director of the Center for Community-Engaged Health Informatics and Data Science and as Vice Dean f or Research at Columbia Nursing. Dr. Bakken is the Editor-in-Chief of the Journal of the American Medical Informatics Association . In this talk\, she will use case examples to illustrate how AI-based innovations can po se threats to epistemic justice and mitigating strategies to overcome epi stemic injustice.\n\nSpeaker:\nSuzanne Bakken\, PhD\, RN\, FAAN\, FACMI\, FIASHI\n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medi cine.yale.edu/event/bids-monthly-seminar-series-bakken/\n DTEND;TZID=America/New_York:20250320T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250320T120000 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar Series UID:1dc1b2a6-3829-4c98-b26b-bc5135a115a1 END:VEVENT BEGIN:VEVENT DESCRIPTION:The rapid expansion of artificial intelligence in clinical med icine has led to novel opportunities for trainees both in shaping their c areer trajectories and providing avenues for research. In this talk\, Dr. Donald Wright will discuss his path from residency in Emergency Medicine at Yale through a research fellowship during the emergence of large lang uage models\, into his current position as a fellow in clinical informati cs. He will discuss the rapid pace of recent innovations and the opportun ities for cross-disciplinary collaboration with data scientists. After th e talk\, he will be joined by Dr. Naga (Sasi) Kanaparthy \, also from the Yale-VA clinical informatics fellowship for a short panel discussion on career opportunities in clinical informatics.\n\nSpeaker:\nDonald Wright\ n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yal e.edu/event/ai-in-medicine-student-interest-group-monthly-seminar-wright/ \n DTEND;TZID=America/New_York:20250327T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250327T120000 LOCATION:Zoom \, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:AI in Medicine Student Interest Group Monthly Seminar UID:cbf495a2-5238-449f-a12c-50e375adcca0 END:VEVENT BEGIN:VEVENT DESCRIPTION:Join us for an insightful talk with Professor Kei-Hoi Cheung o n how AI is transforming environmental health research. Learn how natural language processing (NLP) and large language models (LLMs) help identify emerging water contaminants and assess their impact on public health. Di scover how ontologies enhance AI’s ability to interpret scientific data f or a safer future.\n\nSpeaker:\nKei-Hoi Cheung\n\nAdmission:\nFree\n\nFoo d:\nSnacks\n\nDetails URL:\nhttps://medicine.yale.edu/event/yale-nlpllm-i nterest-group-kei/\n DTEND;TZID=America/New_York:20250403T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250403T163000 LOCATION:ZOOM\, URL: https://yale.zoom.us/j/3555437215 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale NLP/LLM Interest Group UID:cc3777c0-c689-4500-b84d-8a8779a39bfd END:VEVENT BEGIN:VEVENT DESCRIPTION:SPEAKER : Raymond Carroll\, PhD\, Distinguished Professor of S tatistics and Faculty of Nutrition at the Texas A&M University. TITLE : " Nutrition is Important\, A Statistical View” ABSTRACT: I am a hard-core statistician\, not a nutritionist. I have worked on statistical aspects o f nutritional science for many years. I have had the benefit of working w ith brilliant minds in basic science\, epidemiology and of course Statist ics. This has included stops in nutritional basic science\, nutritional e pidemiology\, observational studies and nutritional surveillance. In this informal\, non-mathematical talk\, I will discuss these aspects and give my own comments on such things as the nutritional bullets (kale\, anyone ?) that we see in newspapers on a regular basis\, and the highly multivar iate and complex nature of nutritional intakes. YSPH values inclusion and access for all participants. If you have questions about accessibility o r would like to request an accommodation\, please contact Charmila Fernan des at charmila.fernandes@yale.edu. We will try to provide accommodations requested by March 31\, 2025.\n\nSpeaker:\nRaymond Carroll\, PhD\n\nAdmi ssion:\nFree\n\nFood:\nCoffee\n\nDetails URL:\nhttps://medicine.yale.edu/ event/ysph-biostatistics-seminar-tba-4-8-25-copy-copy/\n DTEND;TZID=America/New_York:20250408T113000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250408T101500 GEO:41.303509;-72.931937 LOCATION:Winslow Auditorium\, 60 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:YSPH Biostatistics: Colin White Memorial Lecture: "Nutrition is Im portant\, A Statistical View” UID:10bdeb75-0f94-4aea-b29f-3f75dc1c5da9 END:VEVENT BEGIN:VEVENT DESCRIPTION:From In Silico to In Vivo: Designing Clinical Decision Support for Serious Illness Communication in the Emergency Department Emergency department visits are often significant inflection points in the health t rajectories of older adults and an opportunity to align medical care with patient goals. Despite this\, competing demands mean that few physicians will have these conversations and large\, randomized trials have failed to identify approaches that change physician behavior. In this talk\, Dr. Adrian Haimovich will (a) motivate the need for patient value elicitatio n in the emergency department setting\, (b) describe electronic health re cord approaches to identify older adults most likely to benefit from thes e discussions\, and (c) explore technological innovations to support pati ents and physicians in the acute care setting. Dr. Adrian Haimovich is Di rector of Geriatric Emergency Medicine at Beth Israel Deaconess Medical C enter and an Assistant Professor of Emergency Medicine at Harvard Medical School. His research is at the intersection of electronic health records data science and geriatric acute care with an emphasis on patient and va lue-centered care.\n\nSpeaker:\nAdrian D. Haimovich\, M.D.\, Ph.D.\n\nAdm ission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/ event/research-in-progress-or-rising-star-seminar-adrian/\n DTEND;TZID=America/New_York:20250410T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250410T120000 LOCATION:ZOOM\, URL: https://yale.zoom.us/j/99141783583 SEQUENCE:0 STATUS:Confirmed SUMMARY:Research in Progress | Rising Star Seminar UID:84dab496-2f58-467c-8104-9369e7079f42 END:VEVENT BEGIN:VEVENT DESCRIPTION:AI is everywhere—but haven’t we been here before? In this semi nar\, Professor Bradley Malin will explore why AI has once again become t he technology du jour in biomedicine. He will present examples of machine learning supporting novel biomedical discoveries\, while also highlighti ng how blind trust in AI can lead to significant societal dilemmas. Profe ssor Malin will demonstrate how these challenges can be represented withi n the AI development and application lifecycle\, allowing them to be iden tified and appropriately addressed. Bradley Malin\, Ph.D.\, is the Accent ure Professor of Biomedical Informatics\, Biostatistics\, and Computer Sc ience at Vanderbilt University\, as well as Vice Chair for Research Affair s in the Department of Biomedical Informatics at Vanderbilt University Me dical Center\, where he founded and directs the AI Discovery & Vigilance to Accelerate Innovation & Clinical Excellence (ADVANCE) Center.\n\nSpeak er:\nBradley Malin\, Ph.D.\n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/bids-monthly-seminar-series-malin/ \n DTEND;TZID=America/New_York:20250417T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250417T120000 LOCATION:Zoom \, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar Series UID:718c90e0-d0af-47ab-a318-062240577912 END:VEVENT BEGIN:VEVENT DESCRIPTION:\nSpeaker:\nAmy Justice\n\nAdmission:\nFree\n\nDetails URL:\nh ttps://medicine.yale.edu/event/yalecde-526-seminar-22/\n DTEND;TZID=America/New_York:20250422T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250422T120000 GEO:41.303666;-72.932218 LOCATION:Yale School of Public Health (LEPH)\, 115\, 60 College Street\, N ew Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale/CDE 526 Seminar: "Time to Stop Using Age Alone as a Criteria for Health Screening" UID:094a8137-cba5-4677-87dc-2e93d0110ce4 END:VEVENT BEGIN:VEVENT DESCRIPTION:Early identification\, accurate diagnosis\, and personalized t reatment have been shown to improve outcomes for patients with critical i llness. Dr. Churpek will discuss how machine learning approaches can be u sed along this spectrum of care for the acute phase of critical illness. He will begin by discussing research supporting the rationale behind the proliferation of rapid response systems around the country and the develo pment of early warning scores to identify impending critical illness. He will then describe his work to develop early warning scores using machine learning\, culminating in interventional studies to evaluate their impac t on outcomes. Next\, Dr. Churpek will discuss the importance of accurate diagnosis for patients with critical illness and how machine learning ha s the potential to enhance diagnostic accuracy. Finally\, he will present recent work using causal machine learning to predict individualized trea tment effects for personalized treatment recommendations in critical illn ess.\n\nSpeaker:\nMatthew M. Churpek\n\nAdmission:\nFree\n\nFood:\nLunch\ n\nDetails URL:\nhttps://medicine.yale.edu/event/ai-in-medicine-churpek/\ n DTEND;TZID=America/New_York:20250424T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250424T120000 LOCATION:ZOOM \, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:AI in Medicine: Student Interest Group Monthly Seminar UID:5399d5a7-5220-4277-9c1e-2244937f0d7a END:VEVENT BEGIN:VEVENT DESCRIPTION:Join us for an exclusive hands-on AI workshop exploring Yale’s Computational Health Performance (CHP) infrastructure\, designed to supp ort cutting-edge AI research with a focus on Large Language Models (LLMs) for medical applications. 💡What You Will Learn: Introduction to CHP and its capabilities Setting up access and configuring your environment Expl oring available services on CHP Fine-tuning LLMs for medical applications The workshop will conclude with a guided application development exercis e\, equipping attendees with the skills to leverage AI for medical innova tion.\n\nSpeakers:\nYujia Zhou\; Vincent Zhang\; Lingfei Qian\; Vipina Ke loth\; Al Pacelli\; Nathaniel Price\n\nAdmission:\nRegistrationFees: Regi stration Required\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale. edu/event/ybic-workshop-series-ai/\n DTEND;TZID=America/New_York:20250429T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250429T123000 GEO:41.304048;-72.930993 LOCATION:1020A\, 101 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:YBIC Workshop Series UID:00c7a39a-e3b4-49d2-a4da-449dcb2d3762 END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nRegistrationFees: Registration Required\n\nFood: \nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/welcome-and-lunc h/\n DTEND;TZID=America/New_York:20250429T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250429T123000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Welcome & Lunch UID:cbc0633a-79a4-43b2-a9f2-40b42a48bbc3 END:VEVENT BEGIN:VEVENT DESCRIPTION:Introduction to CHP and its capabilities Setting up access and configuring your enviroment\n\nSpeakers:\nAl Pacelli\; Nathaniel Price\; Yujia Zhou\n\nAdmission:\nRegistrationFees: Registration Required\n\nDet ails URL:\nhttps://medicine.yale.edu/event/workshop-session-1/\n DTEND;TZID=America/New_York:20250429T143000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250429T130000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Session 1 UID:0c410191-d86b-49e4-aed3-f0c2215a45d9 END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nRegistrationFees: Registration Required\n\nDetai ls URL:\nhttps://medicine.yale.edu/event/break-session/\n DTEND;TZID=America/New_York:20250429T144500 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250429T143000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Break UID:0348c339-b247-4599-8c47-6d3db60fd0dc END:VEVENT BEGIN:VEVENT DESCRIPTION:\nSpeakers:\nVipina Keloth\; Vincent Zhang\; Lingfei Qian\n\nA dmission:\nRegistrationFees: Registration Required\n\nDetails URL:\nhttps ://medicine.yale.edu/event/workshop-session-2/\n DTEND;TZID=America/New_York:20250429T160000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250429T144500 SEQUENCE:0 STATUS:Confirmed SUMMARY:Session 2 UID:98ca8768-0aec-45d2-a47e-9fa83c9832ae END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nRegistrationFees: Registration Required\n\nDetai ls URL:\nhttps://medicine.yale.edu/event/networking-session/\n DTEND;TZID=America/New_York:20250429T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250429T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:Networking UID:6e57495d-e7a3-4b3a-8569-5cf53aeb9e85 END:VEVENT BEGIN:VEVENT DESCRIPTION:For those unable to attend in person please join via zoom: htt ps://yale.zoom.us/j/98011069478 Dr. Black - "Effect of Complementary and Integrative Health Therapies on Long-term Opioid Therapy in Veterans with Chronic Pain." Dr. Ramachandran - " Responses and Reforms to Protect Pub lic Health and Advance Health Justice."\n\nSpeakers:\nReshma Ramachandran \; Anne Black\n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps: //medicine.yale.edu/event/yale-gim-research-in-progress-meeting-amy-justi ce-md-phd/\n DTEND;TZID=America/New_York:20250501T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250501T120000 GEO:41.302200;-72.933362 LOCATION:Hope Memorial Building\, H216\, 315 Cedar Street\, New Haven\, CT \, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale GIM Research in Progress Meeting UID:e3874d62-5f8c-4803-abce-a5e6448dc35a END:VEVENT BEGIN:VEVENT DESCRIPTION:What do people want to know about an AI system in order to tru st it? What kind of information can and do software developers provide? I s there a social consensus on what is needed to hold an AI system account able? We find that AI users want less information (and of a different sor t) than software developers typically provide\, suggesting that consensus is currently limited. This talk draws on interviews and observations wit h AI app users\, developers\, and regulators of health-related AI apps\, conducted during an ongoing NSF-funded collaboration between sociologists \, computer scientists\, and physicians. It ends with a discussion of the implications of these findings for emergent AI guidelines and regulation . Alka Menon\, Ph.D.\, is an Assistant Professor of Sociology at Yale Uni versity\, where her primary research and teaching interests are in the so ciology of science\, medicine\, and technology.\n\nSpeaker:\nAlka Menon\n \nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale .edu/event/research-in-progress-or-rising-star-seminar-menon/\n DTEND;TZID=America/New_York:20250508T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250508T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/99141783583 SEQUENCE:0 STATUS:Confirmed SUMMARY:Research in Progress | Rising Star Seminar UID:5c4cb7f3-d849-4738-b5d9-467503ccc69e END:VEVENT BEGIN:VEVENT DESCRIPTION:This presentation examines how stigmatizing language in EHRs s hapes clinical decision-making and perpetuates racial disparities. Using NLP\, patterns are identified in clinicians’ notes in which stigmatizing descriptors are disproportionately applied to Black patients—labels that assign blame\, imply threat\, or diminish identity. Models reveal that ra ce can be inferred from race-redacted notes\, raising critical questions about algorithmic bias in decision support systems. Dr. Senteio is extend ing this analysis to nursing documentation in Brazil\, offering a cross-n ational perspective on how linguistic bias may emerge across languages an d systems. He also presents his current project to develop a framework fo r equitable public health dashboard design and emphasizes the importance of culturally responsive\, community-engaged research. This work informs Dr. Senteio’s forthcoming book\, Movements Meet Backlash: Perceptions\, C ycles\, and the Struggle for Racial Health Equity \, which argues that co nfronting historical and structural inequities is essential to building a more just digital future in medicine.\n\nSpeaker:\nCharles R. Senteio\, PhD\, MBA\, LCSW\n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhtt ps://medicine.yale.edu/event/bids-monthly-seminar-series-senteio/\n DTEND;TZID=America/New_York:20250515T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250515T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar Series UID:accd184f-0692-4357-97ef-281e4cd25f24 END:VEVENT BEGIN:VEVENT DESCRIPTION:Foundation models (FMs) have emerged as transformative tools i n AI-driven healthcare\, promising unprecedented capabilities for biomedi cal data analysis. In this talk\, Xiaoxiao Li\, PhD will first provide an overview of our recent advances in incorporating transformer-based FMs i nto medical image analysis. Despite their successes\, medical FMs face cr itical challenges\, including biases\, limited interpretability\, insuffi cient adaptability to clinical contexts\, etc. As the focus of this talk\ , she will share our exploration of these challenges\, emphasizing strate gies that significantly enhance fairness\, robustness\, and clinical util ity. Additionally\, Li will share her in-depth analysis on critically exa mining the ongoing debate over whether general-purpose foundation models are justified\, considering their substantial cost\, or if specialized me dical foundation models alone suffice. Lastly\, Li will outline her strat egies to unlock the full potential of trustworthy and impactful AI in hea lthcare. ------- Xiaoxiao Li\, PhD is currently an Assistant Professor in the Department of Electrical and Computer Engineering at the University of British Columbia\, a faculty member at Vector Institute. Li is recogni zed as a Canada Research Chair (Tier II) in responsible AI and a Cifar AI Chair. Li’s research interests primarily lie at the intersection of AI a nd healthcare\, theory and techniques for artificial general intelligence (AGI)\, and AI trustworthiness. Li aims to develop the next-generation r esponsible AI algorithms and systems.\n\nSpeaker:\nXiaoxiao Li\, PhD\n\nA dmission:\nFree\n\nFood:\nSnacks\n\nDetails URL:\nhttps://medicine.yale.e du/event/yale-nlpllm-interest-group/\n DTEND;TZID=America/New_York:20250515T173000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250515T163000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/3555437215 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale NLP/LLM Interest Group UID:12efdc07-d6d8-4221-9040-546bd9a21dfc END:VEVENT BEGIN:VEVENT DESCRIPTION:We’re excited to invite you to an upcoming Yale Biomedical Inf ormatics and Computing (YBIC) workshop focused on leveraging MarketScan m edical data to generate real-world evidence for clinical research. The ev ent will take place on Thursday\, May 22 from 8:30 - 11:30 AM in-person a t 101 College St . Breakfast will be provided. Agenda: 08:30 - 09:00 AM G athering & Breakfast 09:00 - 11:00 AM Workshop Sessions (includes short break) 11:00 - 11:30 AM Panel Discussion This interactive workshop will feature subject matter experts\, use cases and a panel discussion. Facult y from Yale and peer institutions will share their experiences and approa ches to working with claims data in diverse research settings. Whether yo u are new to MarketScan or already integrating claims data into your rese arch\, this workshop will offer valuable perspectives and opportunities f or collaboration.\n\nSpeakers:\nHua Xu\; Xiaomei Ma\; Joseph Ross\; Cary Gross\; Sissi Sun\; Yuntian Liu\; Richa Sharma\; Yechi Zhang\; Lucila Ohn o-Machado\; Yuan Lu\n\nAdmission:\nRegistrationFees: Registration Require d\n\nFood:\nBreakfast\, Coffee\, Tea\n\nDetails URL:\nhttps://medicine.ya le.edu/event/ybic-workshop-series-may22/\n DTEND;TZID=America/New_York:20250522T113000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250522T083000 GEO:41.304048;-72.930993 LOCATION:123A\, 101 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:YBIC Workshop Series UID:5a5dd59f-ae3a-4039-870d-3be869bbc3ae END:VEVENT BEGIN:VEVENT DESCRIPTION:For those unable to attend in person\, please join us via zoom : https://yale.zoom.us/j/98011069478 using the passcode located on the we ekly announcement and calendar invite.\n\nSpeaker:\nAndrew Loza\n\nAdmiss ion:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/eve nt/yale-general-internal-medicine-research-in-progress-meeting/\n DTEND;TZID=America/New_York:20250529T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250529T120000 GEO:41.302200;-72.933362 LOCATION:Hope Memorial Building\, H216\, 315 Cedar Street\, New Haven\, CT \, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale General Internal Medicine Research in Progress Meeting UID:d5cad78d-b014-4505-bea1-0e893759b0e0 END:VEVENT BEGIN:VEVENT DESCRIPTION:Lichao Sun\, PhD\, will present new research on the integratio n of medical foundation models to support clinical decision-making. While current large language model–based tools offer promise\, they often lack the adaptability required in complex and evolving care settings. To addr ess this gap\, Sun and colleagues have developed a generalist\, multi-mod al foundation model capable of performing a wide range of medical tasks. Building on this work\, they introduce a Clinical Agentic AI System that incorporates reinforcement learning to enable autonomous planning\, execu tion\, and refinement of diagnostic and therapeutic strategies in respons e to real-time clinical dynamics. Case studies in radiology demonstrate i mprovements in diagnostic accuracy and efficiency\, offering a vision of AI as a responsive partner in patient care. Lichao Sun\, PhD has extensiv e prior experience in AI agents\, large language models\, trustworthy AI\ , and medical AI. PI Sun has published over 100 papers in major scientifi c venues\, including Nature Medicine\, NeurIPS\, ICML\, ICLR\, KDD\, WWW\ , SIGIR\, CVPR\, ICCV\, ECCV\, ACL\, EMNLP\, NAACL\, AAAI\, and IJCAI. Hi s publications have received more than 16500+ citations\, with an h-index of 59 according to Google Scholar as of June 2025. His research has demo nstrated practical utility and has been integrated into industrial produc ts\, with three 1K stars open-source projects on GitHub. Notably\, one of his papers was shortlisted for the Best Paper IEEE Transactions on Depen dable and Secure Computing 23\, Best Paper Honorable Mention Award at SIG IR’23\, one won the 1st Rank MedFM Challenge at NeurIPS'23\, and the NSF CRII Award. Dr. Sun is the recipient of the 2024 Microsoft Accelerate Fou ndation Models Research Award and the 2024 OpenAI Researcher Access Progr am Award. His work has been featured in several news media outlets\, incl uding Huggingface Daily Papers and others.\n\nSpeaker:\nLichao Sun\, PhD\ n\nAdmission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yal e.edu/event/research-in-progress-or-rising-star-seminar-lichao-sun/\n DTEND;TZID=America/New_York:20250612T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250612T120000 LOCATION:Zoom \, URL: https://yale.zoom.us/j/99141783583 SEQUENCE:0 STATUS:Confirmed SUMMARY:Research in Progress | Rising Star Seminar UID:d9d82100-814c-4020-82f9-b586110b9fb1 END:VEVENT BEGIN:VEVENT DESCRIPTION:http://wnpr.org/programs/yale-cancer-answers For additional in formation and direction about your diagnosis and/or treatment options\, p lease call 1-855-4-SMILOW.\n\nSpeaker:\nSanjay Aneja\n\nAdmission:\nFree\ n\nDetails URL:\nhttps://medicine.yale.edu/event/yale-cancer-answers-390/ \n DTEND;TZID=America/New_York:20250615T200000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250615T193000 LOCATION:WNPR 90.5 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale Cancer Answers UID:204b2998-0865-4952-bb16-c2f79182e66a END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nFood:\nBreakfast\, Coffee\, Lunch\, Snac ks\n\nDetails URL:\nhttps://medicine.yale.edu/event/mbandb-computational- biophysics-and-biochemistry-sympoisum/\n DTEND;TZID=America/New_York:20250617T120000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250617T090000 GEO:41.317985;-72.923668 LOCATION:Bass Center\, 305\, 266 Whitney Avenue\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:MB&B Computational Biophysics & Biochemistry Sympoisum UID:e624dd81-dacd-4cd0-8f2c-ec24b5e1c75f END:VEVENT BEGIN:VEVENT DESCRIPTION:In this talk\, Mohammed AlQuraishi\, PhD\, assistant professor at Columbia University \, presents OpenFold —a fully trainable\, open-so urce\, and hardware-optimized version of AlphaFold. While AlphaFold revol utionized structural biology by predicting protein structures from sequen ce\, it lacks the flexibility to train on new tasks\, is unoptimized for most computing hardware\, and offers limited insight into how training da ta influences accuracy. OpenFold addresses these gaps\, reproducing Alpha Fold’s performance while enabling large-scale prediction campaigns and ne w applications\, such as modeling alternate protein conformations and ant ibody structures. AlQuraishi will also share findings from training OpenF old from scratch\, highlighting new relationships between data diversity and predictive accuracy—and offering a deeper understanding of how protei n folding models learn. Mohammed AlQuraishi\, PhD is an Assistant Profess or in the Department of Systems Biology and a member of Columbia’s Progra m for Mathematical Genomics\, where he works at the intersection of machi ne learning\, biophysics\, and systems biology. The AlQuraishi Lab focuse s on two biological perspectives: the molecular and systems levels. On th e molecular side\, the lab develops machine learning models for predictin g protein structure and function\, protein-ligand interactions\, and lear ned representations of proteins and proteomes. On the systems side\, the lab applies these models in a proteome-wide fashion to investigate the or ganization\, combinatorial logic\, and computational paradigms of signal transduction networks\, how these networks vary in human populations\, an d how they are dysregulated in human diseases\, particularly cancer. AlQu raishi holds undergraduate degrees in Biology\, Computer Science\, and Ma thematics. He earned an M.S. in Statistics and a Ph.D. in Genetics from S tanford University\, and was a Fellow in Systems Biology at Harvard Medic al School prior to joining the Columbia\n\nSpeaker:\nMohammed AlQuraishi\ , PhD\n\nAdmission:\nFree\n\nFood:\nLunch: Boxed Lunch - Sandwiches \n\nD etails URL:\nhttps://medicine.yale.edu/event/bids-monthly-seminar-series- mohammed-alquraishi/\n DTEND;TZID=America/New_York:20250618T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250618T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Cancelled SUMMARY:BIDS Monthly Seminar Series UID:6e4ca22a-8580-4d8b-916f-a8a6fff8e01a END:VEVENT BEGIN:VEVENT DESCRIPTION:We are excited to invite you to attend a special Yale–CZ Biohu b NY event designed to spark scientific exchange and new collaborations b etween our two communities. The event will be held in person at Yale and will bring together Investigators from both institutions for a day of tal ks\, networking\, and focused discussion. The CZ Biohub New York is a col laborative research initiative between Columbia\, Rockefeller\, and Yale Universities. The mission of the CZ Biohub New York is to harness immune system and engineer immune cells for the early detection and eradication of human disease. This event is an opportunity to highlight the innovativ e science happening across both Yale and the Biohub\, while fostering mea ningful connections and potential collaborations. I The planned schedule for the day is as follows: Scientific presentations from Biohub Principal Investigators including Peter Sims\, Evan Paull\, Roham Parsa\, and Sjou kje Van der Stegen Lightning talks (10 min + 5 min Q&A) from Yale Investi gators to introduce their research and connect with Biohub colleagues A n etworking lunch\n\nSpeakers:\nJohn Tsang\; Evan Paull\; Roham Parsa\; Tim Olsen\; Sjouke van der Stegan\; Peter Sims\; Andre Levchenko\; Andres Hi dalgo\; Jennifer Kwan\; Steven Kleinstein\; Gur Yaari\; Sidi Chen\; Etien ne Caron\; Ya-Chi Ho\; Carrie Lucas\; Lauren Sansing\; Andrew Martins\; M ark Lee\n\nAdmission:\nFree\n\nFood:\nCoffee\, Lunch\, Snacks\, Tea\n\nDe tails URL:\nhttps://medicine.yale.edu/event/cz-biohub-ny-at-yale-mini-wor kshop/\n DTEND;TZID=America/New_York:20250709T180000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250709T100000 GEO:41.304215;-72.931754 LOCATION:1116\, 100 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Mini Workshop UID:cc386e0a-9b33-4ba4-8348-b09b2e40532b END:VEVENT BEGIN:VEVENT DESCRIPTION:Large language models (LLMs) are rapidly reshaping biomedical research and healthcare. In this talk\, Qiao Jin\, MD\, will cover four k ey areas: medical AI evaluation\, retrieval-augmented generation (RAG)\, language agents\, and clinical trial matching. He will begin by examining widely used medical AI benchmarks such as PubMedQA and their hidden limi tations. He will then explore RAG as a paradigm shift in biomedical searc h\, highlighting models like MedRAG and i-MedRAG. Jin will also introduce novel AI agents\, including GeneAgent for biomedical knowledge discovery and AgentMD for clinical risk prediction. The talk will conclude with Tr ialGPT\, a first-of-its-kind system that uses LLMs to match patients to c linical trials. Together\, these topics offer both conceptual frameworks and practical insights into the future of LLMs in biomedicine. Qiao Jin\, MD\, is a medical AI researcher at the National Institutes of Health. He developed PubMedQA\, TrialGPT\, and other widely used tools\, with work published in Nature Methods and npj Digital Medicine . He has received mu ltiple national awards and serves on editorial boards in biomedical infor matics.\n\nSpeaker:\nQiao Jin\, MD\n\nAdmission:\nFree\n\nFood:\nLunch\n\ nDetails URL:\nhttps://medicine.yale.edu/event/research-in-progress-or-ri sing-star-seminar-qiao-jin/\n DTEND;TZID=America/New_York:20250710T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250710T120000 LOCATION:ZOOM \, URL: https://yale.zoom.us/j/96550951740?from=addon SEQUENCE:0 STATUS:Confirmed SUMMARY:Research in Progress | Rising Star Seminar UID:a18b556a-1e22-49ee-ac42-69c9f104ee35 END:VEVENT BEGIN:VEVENT DESCRIPTION:Modeling time series of data that are stochastic and irregular ly sampled remains a challenge across multiple fields. This is especially true in medicine\, where numeric and categorical observations are made i n a sparse manner across numerous classes at irregular intervals. Time se ries models well suited for categorical inputs are often not ideal for nu meric inputs\, and vice versa. Furthermore\, sampling of systems is often not performed at random\, and measurement time may reflect important inf ormation about the evolution of the underlying system. Generative modelin g has led to state-of-the-art performance in language processing\, image analysis\, speech recognition\, and more. This talk describes work adapti ng transformer-based architectures to model Electronic Heath Record data. Two models will be presented\, one focusing on adapting a discrete token framework to include both numeric and continuous inputs\, and a second f ocusing on incorporating sequence level properties into the pretraining p rocess for effect estimation and guided decoding. Andrew Loza received hi s PhD from Washington University in St. Louis in biophysics studying mech anisms of collective cell migration using time lapse microscopy coupled w ith computer vision methods and simulation. He completed his MD degree at the Yale University School of Medicine and residency in Internal Medicin e – Pediatrics also at Yale. He then completed a Clinical Informatics fel lowship in the ACGME Yale/VA program with clinical work at the Yale Inter nal Medicine – Pediatrics Clinic. Dr. Loza is a physician-scientist whose research focuses on combining classical statistical methods and deep lea rning to improve disease diagnosis and the delivery of care. His current research focuses on developing statistical and deep learning models of el ectronic health record data to improve risk prediction\, diagnosis\, and disease phenotyping.\n\nSpeaker:\nAndrew Loza\n\nAdmission:\nFree\n\nFood :\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/bids-monthly-se minar-andrew-loza/\n DTEND;TZID=America/New_York:20250717T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250717T120000 LOCATION:Join from PC\, Mac\, Linux\, iOS or Android: https://yale.zoom.us /j/95975389943 \nOr Telephone: 203-432-9666 (2-ZOOM if on-campus) or 646 568 7788 \nOne Tap Mobile: +12034329666\,\,95975389943# US (Bridgeport)\n Meeting ID: 959 7538 9943\nInternational numbers available: https://yale. zoom.us/u/aeGAMHfEIr\, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar UID:e53aeb81-f858-41f3-9f28-e0b23b6da6ca END:VEVENT BEGIN:VEVENT DESCRIPTION:We invite you to the concluding symposium for the Big Data Sum mer Immersion at Yale (BDSY) program. This event marks the culmination of an intensive summer of research and learning by a cohort of exceptional undergraduate scholars from across the country and the world.We will also showcase the impressive work of our students as they present the results of their summer research projects—developed in collaboration with Yale S chool of Public Health mentors—through lightning talks and a poster sessi on. To view the full schedule \, please visit bit.ly/ bdsy2025 .\n\nSpeak ers:\nHarrison Zhou\; Terika McCall\; Harsh Parikh\, PhD\; Peter Clardy\, MD\n\nAdmission:\nFree\n\nFood:\nCoffee\, Lunch\, Tea\n\nDetails URL:\nh ttps://medicine.yale.edu/event/symposium-on-big-data-human-health-and-sta tistics/\n DTEND;TZID=America/New_York:20250724T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250724T090000 GEO:41.317278;-72.922530 LOCATION:Kline Biology Tower\, 219 Prospect Street\, New Haven\, CT\, Unit ed States SEQUENCE:0 STATUS:Confirmed SUMMARY:Symposium on Big Data\, Human Health\, and Statistics UID:4421d250-63ba-4982-beef-b74bb7da71a6 END:VEVENT BEGIN:VEVENT DESCRIPTION:Abstract: This talk presents our approach to virtual cell mode ling by building computational representations of core cellular processes —transcription\, translation\, and cell state dynamics—using specialized models: Epinet for transcription\, NVCell for single-cell multiomic state modeling\, and CodonFM for translation. In this talk\, we focus on Codon FM and introduce a suite of codon-resolution language models trained on o ver 120 million coding sequences from 22\,000 species. Unlike traditional protein models that ignore synonymous codon variation\, cdsFM captures t he functional and regulatory impact of codon choice\, learning the struct ure of the genetic code and offering new insights into how coding sequenc es shape protein expression in the cell.\n\nSpeaker:\nLaksshman Sundaram\ n\nAdmission:\nFree\n\nFood:\nYou must register to receive a boxed lunch at the event.\nA registration sheet will be utilized at the event.\n\nDet ails URL:\nhttps://medicine.yale.edu/event/laksshman-sundaram-gives-speci al-ycccsei-seminar/\n DTEND;TZID=America/New_York:20250807T131500 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250807T120000 GEO:41.304215;-72.931754 LOCATION:1116\, 100 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:AT CAPACITY - Laksshman Sundaram gives Special YCC/CSEI Seminar- R EGISTRATION CLOSED UID:e3ae42ac-eb16-498f-a764-9848d9255d3a END:VEVENT BEGIN:VEVENT DESCRIPTION:Christopher Longhurst MD\, MS\, FAAP\, FACMI is an internation ally recognized scholar\, educator\, and administrative leader in the fie lds of quality\, patient safety\, and clinical informatics\, especially h ealthcare AI. He currently serves as the chief clinical & innovation offi cer at UC San Diego Health\, where he provides leadership to medical staf f\, ensuring that standards and protocols are in place to provide the hig hest quality of care to patients\, and positions digital transformation a s a key tool in these efforts. As the executive director for the Joan & I rwin Jacobs Center for Health Innovation\, Dr. Longhurst also has respons ibility for the artificial intelligence (AI) portfolio across the health system. Within the UC San Diego School of Medicine\, Dr. Longhurst serves as an associate dean to help align education and research missions withi n the clinical environment and lead the journey to become a highly reliab le\, learning health system. As a faculty member in the Departments of Bi omedical Informatics and Pediatrics\, Dr. Longhurst also maintains an act ive clinical practice as a newborn hospitalist and speaks nationally and internationally about his innovations in the field.\n\nSpeaker:\nChristop her Longhurst MD\, MS\, FAAP\, FACMI \n\nAdmission:\nFree\n\nFood:\nLunch \n\nDetails URL:\nhttps://medicine.yale.edu/event/bids-monthly-seminar-lo nghurst/\n DTEND;TZID=America/New_York:20250821T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250821T120000 LOCATION:Join from PC\, Mac\, Linux\, iOS or Android: https://yale.zoom.us /j/95975389943 Or Telephone: 203-432-9666 (2-ZOOM if on-campus) or 646 56 8 7788 \n\nOne Tap Mobile: +12034329666\,\,95975389943# US (Bridgeport) M eeting ID: 959 7538 9943 International numbers available: https://yale.zo om.us/u/aeGAMHfEIr SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar UID:b6d3d346-513e-4a3d-881a-4a59788a5e45 END:VEVENT BEGIN:VEVENT DESCRIPTION:Tick Talk\n\nSpeaker:\nJoseph Canterino\n\nAdmission:\nFree\n\ nDetails URL:\nhttps://medicine.yale.edu/event/general-internal-medicine- grand-rounds-tick-talk/\n DTEND;TZID=America/New_York:20250904T083000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250904T073000 SEQUENCE:0 STATUS:Confirmed SUMMARY:General Internal Medicine Grand Rounds\, Tick Talk UID:74ccf231-e8ff-43f1-8df8-a15f89096000 END:VEVENT BEGIN:VEVENT DESCRIPTION:Join us in a virtual panel event on September 11\, 2025 at 11: 00 am-12:00 pm ET focused on approaches to developing\, crafting\, and wr iting an NIH specific aims page\, featuring brief presentations by facult y investigators followed by discussion and Q&A with audience members. Thi s event is part of CIRA’s Early Career Scientists Networking Forum (CIRA- ECS) initiative\, co-sponsored by the Yale Global HIV/AIDS Research Netwo rk (GARNER). The forum aims to create a space for CIRA and GARNER-affilia ted early-career researchers to share works-in-progress\, grant ideas\, m anuscripts\, professional development topics\, and foster opportunities f or networking and collaboration.Panelists:• Amy Justice\, Yale School of Medicine• Nicola Hawley\, Yale School of Public HealthModerator: • Jeffre y Wickersham\, Yale School of Medicine We welcome questions in advance fo r the panelists and moderator that can be submitted through the Zoom regi stration form below. Register to attend virtually via Zoom: https://yale. zoom.us/meeting/register/pRikhJlgR2q51tIP1Irmyg#/registration\n\nSpeakers :\nJeffrey Wickersham\; Amy Justice\; Nicola Hawley\n\nAdmission:\nFree\n \nDetails URL:\nhttps://medicine.yale.edu/event/cira-early-career-scienti sts-panel-nih-specific-aims/\n DTEND;TZID=America/New_York:20250911T120000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250911T110000 LOCATION:URL: https://yale.zoom.us/meeting/register/pRikhJlgR2q51tIP1Irmyg #/registration SEQUENCE:0 STATUS:Confirmed SUMMARY:CIRA-YIGH Early-Career Scientists Panel UID:3907136e-0e89-452b-9dbd-5b2a2fdea208 END:VEVENT BEGIN:VEVENT DESCRIPTION:Li Song\, PhD\, assistant professor at Dartmouth \, will prese nt computational methods for comprehensive immune receptor and microbiome analysis from standard sequencing data. Sequencing data contains rich im mune and microbiome information\, but common RNA-seq workflows rely heavi ly on reference genomes and miss underrepresented features such as immune receptors and microbes. Song will discuss TRUST4\, which reconstructs T- cell receptor (TCR) and B-cell receptor (BCR) sequences from bulk and sin gle-cell RNA-seq data\, and T1K\, for genotyping highly polymorphic genes such as killer immunoglobulin-like receptors (KIRs) and human leukocyte antigen (HLA) genes. She will also introduce Centrifuger\, a taxonomic cl assification tool using a novel run-block compression scheme to store mas sive microbial genome databases efficiently. Centrifuger enables accurate s pecies-level classification and reveals microbiome composition. These too ls expand the scope of low-cost sequencing data\, enabling integrated imm une and microbiome insights.\n\nSpeaker:\nLi Song\, PhD \n\nAdmission:\nF ree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/rese arch-in-progress-or-rising-star-seminar-lisong/\n DTEND;TZID=America/New_York:20250911T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250911T120000 LOCATION:Join from PC\, Mac\, Linux\, iOS or Android: https://yale.zoom.us /j/96550951740?from=addon\nOr Telephone：203-432-9666 (2-ZOOM if on-campus ) or 646 568 7788\nOne Tap Mobile: +12034329666\,\,96550951740# US (Bridg eport)\n\nMeeting ID: 965 5095 1740\nInternational numbers available: htt ps://yale.zoom.us/u/aQeyEAiAD\n\nFor H.323 and SIP information for video conferencing units please click here: https://yale.service-now.com/it?id= support_article&sys_id=434b72d3db9e8fc83514b1c0ef961924 SEQUENCE:0 STATUS:Confirmed SUMMARY:Research in Progress: Rising Star Seminar UID:19483672-60d4-4cb1-98ca-0bb8bba25d85 END:VEVENT BEGIN:VEVENT DESCRIPTION:Join us for the next seminar in our NLP/LLM Interest Group\, f eaturing cutting-edge research at the intersection of language models\, e mbeddings\, and multimodal learning. Featured Talks: A Vector is Worth 1\ ,000 Words: Training Large Language Models to Interpret Embedding Spaces Speaker: Brian Ondov\, PhD\, Associate Research Scientist Empowering Mult imodal Large Language Models for Grounded ECG Understanding with Time Ser ies and Images Speaker: Xiang Lan\, PhD\, Postdoctoral Associate ⬅️ Downl oad the flyer for abstract details (PDF) 💌 Subscribe to our mailing list to stay informed about future events.\n\nSpeakers:\nBrian Ondov\; Xiang Lan\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/ nlpllm-interest-group-1/\n DTEND;TZID=America/New_York:20250915T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250915T160000 LOCATION:URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20250915T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group Session UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Danielle Mowery\, PhD\, is a collaborative investigator that d evelops natural language processing (NLP) and generative artificial intel ligence (AI) solutions for processing clinical texts – i.e.\, clinical no tes\, chatbots\, and transcribed texts – to support clinical and translat ional research. She leverages NLP\, data science\, machine learning\, and computational methods to integrate and analyze information from unstruct ured texts and structured clinical data to help clinical investigators be tter understand disease burden\, treatment efficacy\, and clinical outcom es. Furthermore\, her solutions focus on helping patients and clinicians make better decisions at the point of care whether it’s in a traditional health system setting or through digital health services within a patient ’s home. Her work aims to uncover scientific discoveries\, identify actio nable healthcare knowledge\, and optimize translation of research into pa tient care. In this talk\, she will review key use cases in which NLP and generative AI are innovating in key areas of basic science\, applied cli nical informatics\, and population health.\n\nSpeaker:\nDanielle L. Mower y\, PhD\, MS\, MS\, FAMIA \n\nAdmission:\nFree\n\nDetails URL:\nhttps://m edicine.yale.edu/event/nlpllm-interest-group-mowery/\n DTEND;TZID=America/New_York:20250922T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250922T160000 LOCATION:URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20250922T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Andrew Loza\, MD\, PhD\, will introduce Comet—a family of tran sformer models trained on Epic Cosmos\, an unprecedented dataset containi ng 16.3 billion encounters across 300 million patient records from 310 he alth systems\, representing 115 billion medical events from 118 million p atients. Comet autoregressively predicts the next medical event to simula te patient health timelines. Across 78 real-world tasks including diagnos is prediction\, disease prognosis\, and healthcare operations\, Comet out performed or matched task-specific supervised models without requiring fi ne-tuning. Our results demonstrate that generative medical event foundati on models can effectively capture complex clinical dynamics\, providing a generalizable framework to support clinical decision-making and improve patient outcomes.\n\nSpeaker:\nAndrew Loza\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/nlpllm-interest-group-3/\n DTEND;TZID=America/New_York:20250929T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250929T160000 LOCATION:Zoom - Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20250929T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:The rapid growth of scientific publications has made literatur e discovery increasingly challenging. While traditional search engines an d recent chatbots provide access and summaries\, they remain limited for deeper exploration. In this talk\, Huan He\, PhD will introduce the conce pt of AI agents as "co-pilots" for literature discovery\, using the MedVi z system as a case study. He will demonstrate how multi-agent architectur es and large-scale visualizations can transform literature search from a passive query-response model into an active\, exploratory process.\n\nSpe aker:\nHuan He\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale .edu/event/nlpllm-interest-group-4/\n DTEND;TZID=America/New_York:20251006T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251006T160000 LOCATION:Passcode Required: 849811\, URL: https://yale.zoom.us/j/935999419 69 RECURRENCE-ID;TZID=America/New_York:20251006T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-5/\n DTEND;TZID=America/New_York:20251013T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251013T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251013T160000 SEQUENCE:0 STATUS:Cancelled SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:The evidence base for LLMs in digestive diseases shows wide pe rformance variability\, underscoring safety risks and the need for rigoro us evaluation. In this talk\, Mauro Giuffrè\, MD will overview his main c ontributions in the field: a systematic review that quantified accuracy r anges and highlighted methodological gaps\; a guideline-grounded study sh owing that retrieval-augmented and fine-tuned GPT-4 markedly improve open -ended answer quality and treatment selection in patients with Hepatitis C Virus\; an “expert-of-experts” verification framework (EVAL) that align s automated grading with human experts and boosts correctness via rejecti on sampling\; and a randomized simulation trial (GutGPT) revealing that b etter usability does not automatically translate into adoption\, pointing to trust and workflow integration as key levers for impact.\n\nAdmission :\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/nlpllm-interest- group-giuffre/\n DTEND;TZID=America/New_York:20251020T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251020T160000 LOCATION:Zoom: Passcode Required: 849811 \, URL: https://yale.zoom.us/j/93 599941969 RECURRENCE-ID;TZID=America/New_York:20251020T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:From Compound Figures to Composite Understanding: Developing a Multi-Modal LLM from Biomedical Literature with Medical Multiple-Image B enchmarking and Validation In healthcare\, disease diagnostics and longit udinal patient monitoring require clinicians to synthesize information ac ross multiple images from different modalities or time points\, yet this multi-image reasoning remains a significant gap for most current multi-mo dal LLMs. This capability gap persists due to a critical bottleneck: the lack of large-scale\, high-quality annotated training data for medical mu lti-image understanding. This study aims to address this scarcity by leve raging compound figures from biomedical literature. We devised a novel fi ve-stage\, context-aware instruction generation pipeline to create the PM C-MI-Dataset comprising over 260\,000 compound images\, and subsequently developed M³LLM\, a medical multi-image multi-modal LLM. For a comprehens ive evaluation\, we also constructed the expert-validated PMC-MI-Bench. M ³LLM significantly outperforms state-of-the-art general-purpose and speci alized MLLMs\, achieving superior performance on diverse tasks of the PMC -MI-Bench and public benchmarks like OmniMedVQA and MMMU-Med. Furthermore \, clinical validation on the MIMIC longitudinal chest X-ray dataset conf irms its superior performance in real-world tasks\, including disease dia gnosis and progression prediction. Our study establishes a scalable parad igm for this task\, and the model\, dataset\, and benchmark will be publi cly released.\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale. edu/event/nlpllm-interest-group-7/\n DTEND;TZID=America/New_York:20251027T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251027T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251027T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Large language models hold enormous potential for transforming healthcare\, but their deployment is often bottlenecked by unstructured data\, fragmented pipelines\, and inconsistent model-data alignment. Nimb lemind.AI addresses these challenges with an agentic AI framework that au tomates the full clinical data lifecycle from ingestion and de-identifica tion to inference and interpretability. Building on the paper\, “Agentic AI Framework for End-to-End Medical Data Inference”\, the talk will discu ss how specialized agents collaborate to process multimodal data\, link s tructured EHR fields with clinical narratives\, and route tasks to the mo st appropriate foundation or domain model. This framework demonstrates ho w autonomous agent coordination can turn LLMs into operational tools to c ontextualize patient records\, ensure reproducibility\, and generate tran sparent explanations of model outputs. The talk will wrap up with a demo of Nimblemind.AI's new platform\, NimbleLabs\, where users can add a simp le clinical description and relevant data to generate a fully operational \, specialty-specific predictive model ready for real-world clinical envi ronments. Navin Kumar\, PhD is the co-founder of Nimblemind.AI\, a compan y building agentic AI systems to make clinical data interoperable and act ionable. Born and raised in Singapore\, Kumar earned their PhD at Yale Un iversity under Nicholas Christakis \, publishing over 60 papers and secur ing more than $1M in research funding on AI-driven approaches to populati on health. Before founding Nimblemind.AI\, they led data science and AI i nitiatives at NYC Health + Hospitals\, the nation’s largest public health care system\, and deployed predictive models that improved chronic diseas e screening and reduced missed appointments across over one million patie nts. Witnessing firsthand how data inefficiency limits equitable care\, K umar launched Nimblemind.AI to build scalable\, transparent AI infrastruc ture that improves outcomes\, especially for minority populations.\n\nSpe aker:\nNavin Kumar\, PhD\n\nAdmission:\nFree\n\nDetails URL:\nhttps://med icine.yale.edu/event/nlpllm-interest-group-8/\n DTEND;TZID=America/New_York:20251103T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251103T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251103T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Talk Title: RDMA: Cost Effective Agent-Driven Rare Disease Dis covery within Electronic Health Record Systems Abstract: Rare diseases af fect 1 in 10 Americans\, yet standard ICD coding systems fail to capture these conditions in electronic health records (EHR)\, leaving crucial inf ormation about rare diseases\, their clinical presentations\, and phenoty pic patterns buried in unstructured clinical notes. Current automated ext raction approaches struggle with medical abbreviations\, miss implicit ph enotype mentions\, raise privacy concerns through cloud processing\, and lack the clinical reasoning abilities needed for accurate identification of rare disease presentations in human patients. We present Rare Disease Mining Agents (RDMA)\, a framework that mirrors how clinical experts appr oach rare disease identification by systematically connecting clinical ob servations directly to standardized ontologies like Orphanet and Human Ph enotype Ontology. RDMA handles clinical abbreviations\, recognizes implic it phenotype patterns\, and applies contextual reasoning locally on stand ard hardware to extract and code rare disease information with supporting textual evidence. This approach reduces privacy risks while improving F1 performance by over 30\% and decreasing inference costs 10-fold\, achiev ing high precision (89\%) in rare disease mining and coding. By enabling clinicians to access systematically coded rare disease information with e xplicit evidence from EHR systems without cloud-based privacy risks\, RDM A supports identification and documentation of rare conditions. Available at https://github.com/jhnwu3/RDMA. John Wu is a a Ph.D student in the CS department at the University of Illinois\, currently advised by Professo r Jimeng Sun . His main focus is on building agentic systems for healthca re settings\, whether that be low resource (i.e rare diseases)\, interpre tability\, or clinical predictive modeling. He actively maintains PyHealt h \, and leads a community of open-source researchers\, trying to build m ore reproducible healthcare solutions. His work is currently supported by the NSF GRFP.\n\nSpeaker:\nJohn Wu\n\nAdmission:\nFree\n\nDetails URL:\n https://medicine.yale.edu/event/nlpllm-interest-group-johnwu/\n DTEND;TZID=America/New_York:20251110T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251110T160000 LOCATION:Join via Zoom: https://yale.zoom.us/j/91284647043?pwd=SHB0bu8FRja YFhJmpxYRKUDXlINIYA.1\n\nPassword: 159239\n\nOr Telephone：203-432-9666 (2 -ZOOM if on-campus) or 646 568 7788\n One Tap Mobile: +12034329666\,\, 91284647043# US (Bridgeport)\n\n Meeting ID: 912 8464 7043\n Intern ational numbers available: https://yale.zoom.us/u/ac8x2d0qLF\n\, URL: htt ps://yale.zoom.us/j/91284647043?pwd=SHB0bu8FRjaYFhJmpxYRKUDXlINIYA.1 RECURRENCE-ID;TZID=America/New_York:20251110T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group: RDMA UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-10/\n DTEND;TZID=America/New_York:20251117T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251117T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251117T160000 SEQUENCE:0 STATUS:Cancelled SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-11/\n DTEND;TZID=America/New_York:20251124T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251124T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251124T160000 SEQUENCE:0 STATUS:Cancelled SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:This session will feature two exciting talks: 1. Rethinking Re trieval-Augmented Generation for Medicine: A Large-Scale\, Systematic Exp ert Evaluation and Practical Insights by Hyunjae Kim\, PhD Abstract: Retr ieval-augmented generation (RAG) is widely adopted to keep medical LLMs c urrent and verifiable\, yet its effectiveness remains unclear. We present the first end-to-end\, expert annotated evaluation of RAG in medicine\, systematically assessing the full pipeline across three stages: evidence retrieval\, evidence selection\, and response generation. Eighteen medica l experts provided 80\,502 annotations across 800 model outputs on 200 cl inical queries.Contrary to expectations\, conventional RAG often degraded performance—only 22% of retrieved passages were relevant\, evidence sele ction was weak\, and factuality dropped up to 6%. However\, simple strate gies like evidence filtering and query reformulation improved performance by up to 12%. Our findings challenge current RAG assumptions and highlig ht the need for deliberate system design in medical AI applications. 2. T opicForest: Embedding-Driven Hierarchical Clustering and Labeling for Bio medical Literature by Chia-Hsuan Chang\, PhD Abstract: The vast and compl ex landscape of biomedical literature presents significant challenges for organization and interpretation. Current embedding-based topic models li ke BERTopic are limited to flat\, single-granularity clusters\, failing t o capture the inherently nested\, hierarchical structure of scientific su bjects. We introduce TopicForest\, a novel framework that captures this n atural hierarchy by building a "forest of topic trees" directly from text embeddings. TopicForest delivers high-quality topic clustering comparabl e to state-of-the-art flat models while providing the essential multi-sca le resolution they lack. Through recursive topic labeling\, the framework achieves efficient token usage and practical scalability for large corpo ra. This design provides researchers with an effective tool for exploring and visualizing hierarchical biomedical knowledge landscapes.\n\nSpeaker s:\nHyunjae Kim\; Chia-Hsuan Chang\n\nAdmission:\nFree\n\nDetails URL:\nh ttps://medicine.yale.edu/event/nlpllm-interest-group-12/\n DTEND;TZID=America/New_York:20251201T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251201T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251201T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:This session will feature two exciting talks: A Collaborative Reasoning Agent-based Framework with Built-in Verification for Safe Medic al Decision-Making by Fan Ma\, PhD Abstract: Large language models (LLMs) have demonstrated expert-level capabilities on medical benchmarks\, yet translating these achievements into clinical practice is impeded by persi stent risks of hallucination and a lack of verifiable reasoning. While em erging agentic frameworks have begun to address these limitations through multi-step planning\, existing systems often prioritize performance opti mization over rigorous safety checks and fail to emulate the collective d ecision-making of multidisciplinary teams. To address these critical gaps \, we introduce OpenDx\, a multi-agent framework designed to bridge the d ivide between experimental prototypes and reliable clinical decision supp ort. OpenDx is built upon three core principles: collaboration among spec ialized agents that simulate distinct clinical roles\, integrated verific ation modules that strictly cross-check outputs for safety and consistenc y\, and an architectural alignment with clinical auditability standards. We present the design and evaluation of OpenDx\, demonstrating how struct ured collaboration significantly enhance reliability compared to baseline models. Our work advocates for a new paradigm of trustworthy medical AI\ , where performance gains are inseparable from the interpretability and s afety assurances required for frontline healthcare deployment. A Federate d and Parameter-Efficient Framework for Large Language Model Training in Medicine: Applications to Clinical Information Extraction by Anran Li\, P hD Abstract: Large language models (LLMs) are advancing medical applicati ons such as patient question answering and diagnosis. Yet extracting stru ctured information from unstructured clinical narratives across healthcar e systems remains challenging. Current LLMs struggle with such clinical i nformation extraction (IE) due to complex language\, limited annotations\ , and data silos. We present a federated\, model-agnostic framework for t raining LLMs in medicine\, applied to clinical IE. The proposed Fed-MedLo RA enables parameter-efficient federated fine-tuning by transmitting only low-rank adapter parameters\, substantially reducing communication and c omputation costs. Accuracy was assessed across five patient cohorts throu gh comparisons with baselines for LLMs under (1) in-domain training and t esting\, (2) external patient cohorts\, and (3) a case study on new-site adaptation using real-world clinical notes.\n\nSpeakers:\nFan Ma\; Anran Li\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/n lpllm-interest-group-13/\n DTEND;TZID=America/New_York:20251208T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251208T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251208T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:A Prompt Library for Efficient Clinical Entity Recognition Usi ng Large Language Models by Yang Ren\, PhD Abstract: Large Language Model s (LLMs) hold strong potential for clinical information extraction (IE)\, but their evaluation is often limited by manually crafted prompts and th e need for annotated data. We developed an automated framework that extra cts entity-level schema information from published clinical IE studies to construct structured prompts. Using literature covering 44 diseases and over 100 entities\, we generated prompts to evaluate multiple LLMs under few-shot and fine-tuned settings. Compared to baselines using generic pro mpts\, models prompted with schema-derived information consistently outpe rformed across tasks. Our results demonstrate the value of structured pro mpting for robust and reproducible LLM evaluation in diverse clinical IE applications.\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale. edu/event/nlpllm-interest-group-14/\n DTEND;TZID=America/New_York:20251215T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251215T160000 LOCATION:Zoom: Passcode Required - Please Email Sooyoun Tan \, URL: https ://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251215T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:This session will feature two exciting talks: 1. Accelerating Cohort Identification from EHRs with Biomedical Knowledge and LLMs by Lin gfei Qian\, PhD Abstract ： Identifying eligible patients from electronic health records (EHRs) is a key challenge in clinical research. We present a framework that combines large language models (LLMs)\, Text-to-SQL\, a nd retrieval-augmented generation (RAG) to streamline cohort identificati on. Eligibility criteria are first decomposed and partially translated in to structured queries via Text-to-SQL\, providing a preliminary selection from OMOP-formatted EHR data. The core innovation focuses on RAG/QA to r etrieve and assess patient-level evidence from both clinical notes and st ructured tables\, emphasizing nuanced evaluation of complex criteria like disease chronicity\, lab thresholds\, and clinical stability\, while sup porting interactive cohort exploration and detailed patient-level evidenc e review. This workflow reduces manual effort\, improves accuracy\, and o ffers a scalable\, clinically grounded solution for EHR-based cohort iden tification. 2. An Information Extraction Approach to Detecting Novelty of Biomedical Publications by Xueqing Peng\, PhD Abstract : Scientific nove lty plays a critical role in shaping research impact\, yet it remains inc onsistently defined and difficult to quantify. Existing approaches often reduce novelty to a single measure\, failing to distinguish the specific types of contributions (such as new concepts or relationships) that drive influence. In this study\, we introduce a semantic measure of novelty ba sed on the emergence of new biomedical entities and relationships within the conclusion sections of research articles. Leveraging transformer-base d named entity recognition (NER) and relation extraction (RE) tools\, we identify novel findings and classify articles into four categories: No No velty\, Entity-only Novelty\, Relation-only Novelty\, and Entity-Relation Novelty. We evaluate this framework using citation counts and Journal Im pact Factors (JIF) as proxies for research influence. Our results show th at Entity-Relation Novelty articles receive the highest citation impact\, with relation novelty more closely aligned with high-impact journals. Th ese findings offer a scalable framework for assessing novelty and guiding future research evaluation.\n\nSpeakers:\nLingfei Qian\; Xueqing Peng\n\ nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/nlpllm -interest-group-15/\n DTEND;TZID=America/New_York:20251222T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251222T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251222T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-16/\n DTEND;TZID=America/New_York:20251229T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251229T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20251229T160000 SEQUENCE:0 STATUS:Cancelled SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-17/\n DTEND;TZID=America/New_York:20260105T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260105T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260105T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-18/\n DTEND;TZID=America/New_York:20260112T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260112T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260112T160000 SEQUENCE:0 STATUS:Cancelled SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-19/\n DTEND;TZID=America/New_York:20260119T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260119T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260119T160000 SEQUENCE:0 STATUS:Tentative SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-20/\n DTEND;TZID=America/New_York:20260126T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260126T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260126T160000 SEQUENCE:0 STATUS:Cancelled SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-21/\n DTEND;TZID=America/New_York:20260202T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260202T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260202T160000 SEQUENCE:0 STATUS:Cancelled SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Title: Diagnostic Accuracy and Clinical Reasoning of Multiple Large Language Models Abstract: Large language models are increasingly us ed for mental health–related questions\, yet their performance in psychia try - where diagnosis depends heavily on narrative interpretation and cli nical reasoning - remains poorly understood. In this talk\, I’ll present a mixed-methods evaluation of four contemporary LLMs on 196 psychiatric c ase vignettes\, combining large-scale diagnostic accuracy metrics with cl inician-rated assessments of diagnostic reasoning. We find that models ca n achieve high diagnostic accuracy on vignettes\, but - crucially - that clinician-rated reasoning quality is far more predictive of diagnostic co rrectness than surface-level data extraction. These findings suggest that evaluating how models reason\, not just what they predict\, is essential for understanding their potential role in psychiatric decision support. Kevin Jin is a third-year PhD student in the Interdepartmental Program in Computational Biology and Biomedical Informatics at Yale University. He is advised by Hua Xu in the Clinical NLP Lab\, a research group in the De partment of Biomedical Informatics and Data Science at Yale School of Med icine. He completed his undergraduate work at Johns Hopkins University\, receiving a B.S. in Molecular and Cellular Biology in 2020. He is support ed by the NSF Graduate Research Fellowship.\n\nSpeaker:\nKevin Jin\n\nAdm ission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/nlpllm-int erest-group-22/\n DTEND;TZID=America/New_York:20260209T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260209T160000 LOCATION:Zoom link and passcode will be share on an email RECURRENCE-ID;TZID=America/New_York:20260209T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Title: Rethinking User Interface Design in the Era of AI Agent s Abstract: Artificial intelligence agents are rapidly reshaping how user s interact with digital systems. From embedded copilots to autonomous tas k executors\, agents are no longer confined to chat interfaces—they are b ecoming integral components of modern user interfaces. In this talk\, we will share a series of real-world cases and practical lessons drawn from building agent-driven systems in research and data-intensive environments . We will examine how agents are currently embedded into interfaces\, wha t architectural decisions influence usability and trust\, and what design trade-offs emerge when combining autonomy with human control. We will al so discuss how AI agent tools themselves are transforming the UI design w orkflow—from rapid prototyping to code generation and interaction simulat ion. Huan He\, PhD \, is a research scientist in biomedical informatics a nd data science at Yale University School of Medicine. His primary resear ch areas revolve around visual analytics and their applications in health care-related research. Currently\, his work is focused on designing and d eveloping visual analytics systems using natural language processing (NLP ) and machine learning (ML) technologies\, with the goal of facilitating data exploration for health-related clinical questions.\n\nSpeaker:\nHuan He\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/ nlpllm-interest-group-23/\n DTEND;TZID=America/New_York:20260216T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260216T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260216T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Title: The Evolution and Future of Ocular Image-Based Foundati on Models Abstract: This talk reviews the current landscape of ocular ima ge-based foundation models and examines emerging future directions. In th is talk\, I will discuss how large-scale pretraining has enabled improved generalization\, label efficiency\, and cross-disease performance in ret inal imaging tasks. Beyond current capabilities\, I will explore key tren ds shaping the next phase of development\, including modality-specific ve rsus multimodal architectures\, global-scale pretraining across diverse p opulations\, and integration with language models for clinical reasoning. Finally\, I will address benchmarking\, validation\, and translational c hallenges that must be addressed to move foundation models from research innovation to real-world ophthalmic care. Yih Chung Tham\, PhD\, is a Pre sidential Young Professor and a clinician scientist in the Department of Ophthalmology at the Yong Loo Lin School of Medicine\, National Universit y of Singapore (NUS). At NUS Medicine’s Centre for Innovation & Precision Eye Health\, he holds dual leadership roles as Co-Lead for Population Da ta Science and Program Director for Optometry Education. His research foc uses on big data analytics\, ocular imaging\, deep learning\, and large l anguage models in ophthalmology. He has published more than 350 peer-revi ewed articles in leading journals such as Nature Medicine\, Nature Biomed ical Engineering\, Nature Aging\, Lancet Digital Health\, and Ophthalmolo gy\, with an H-index of 65. Among his most influential works is the Globa l Glaucoma Burden study\, one of the most highly cited ophthalmology-rela ted papers of all time\, with over 8\,500 citations. Since 2021\, he has been consistently recognized among the world’s top 2% most cited scientis ts.\n\nSpeaker:\nYih Chung Tham\, PhD\n\nAdmission:\nFree\n\nDetails URL: \nhttps://medicine.yale.edu/event/nlpllm-interest-group-24/\n DTEND;TZID=America/New_York:20260224T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260224T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260224T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Title: HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmen ted Generation Abstract: Embedding geometry fundamentally affects retriev al quality\, yet dense retrievers for retrieval-augmented generation (RAG ) remain confined to Euclidean space. Natural language has hierarchical s tructure from broad topics to specific entities that Euclidean embeddings fail to preserve\, causing semantically distant documents to appear spur iously similar and increasing hallucination risk. We introduce hyperbolic dense retrieval with two model variants in the Lorentz model: HyTE-FH\, a fully hyperbolic transformer\, and HyTE-H\, a hybrid architecture proje cting pre-trained Euclidean embeddings into hyperbolic space. To prevent representational collapse during sequence aggregation\, we introduce the Outward Einstein Midpoint\, a geometry-aware pooling operator that provab ly preserves hierarchical structure. On MTEB\, HyTE-FH outperforms equiva lent Euclidean baselines. On RAGBench\, HyTE-H achieves up to 29% gains o ver Euclidean baselines in context and answer relevance using substantial ly smaller models than current state-of-the-art retrievers. Hyperbolic re presentations encode document specificity through norm-based separation\, with over 20% radial increase from general to specific concepts\, a prop erty absent in Euclidean embeddings. Hiren Madhu a second year PhD studen t at Yale CS \, advised by Professor Smita Krishnaswamy and Professor Rex Ying . Earlier\, he was an ECE pre-doctoral research fellow in Electrica l Communication Engineering Department at the Indian Institute of Science \, Bengaluru. He worked with Sundeep Prabhakar Chepuri on unsupervised re presentation learning for simplicial complexes. He began his research jou rney at LDRP Institute of Technology and Research (BE in Computer Enginee ring) under the guidance of Sandip Modha and Thomas Mandl\, where he focu sed on the detection of hate speech in public conversational threads on s ocial media. His primary research interest is encoding the geometric indu ctive biases into foundation models. Previously\, he worked on simplicial representation learning without labels.\n\nSpeaker:\nHiren Madhu\n\nAdmi ssion:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/nlpllm-inte rest-group-25/\n DTEND;TZID=America/New_York:20260302T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260302T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260302T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:Title: OpenClaw: A Prospective View on its Current Abilities a nd Potential Medical Field Application Abstract: OpenClaw (formerly MoltB ot) is one of the newest AI technologies to grab the attention of develop ers\, business owners\, and tech enthusiasts across the internet. Perhaps most profoundly recognized for supporting the bots behind MoltBook---the social media platform entirely populated and used by AI---OpenClaw is ad vertised as the next step in AI’s developmental progression\, where model s stop being only chatbots and gain the capability to undertake delegated tasks fully from start to finish. As an autonomous virtual AI assistant\ , OpenClaw brings many potential use cases to the medical field\, along w ith certain concerns of its security and potential for malicious activity . This discussion will explore considerable applications to both clinical scenarios and tech-infrastructure support. Jeffrey Li is an alumnus of B oston University\, graduating in 2025 with majors in Computer Science and Economics.\n\nSpeaker:\nJeffrey Li\n\nAdmission:\nFree\n\nDetails URL:\n https://medicine.yale.edu/event/nlpllm-interest-group-26/\n DTEND;TZID=America/New_York:20260309T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260309T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260309T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-27/\n DTEND;TZID=America/New_York:20260316T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260316T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260316T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-28/\n DTEND;TZID=America/New_York:20260323T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260323T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260323T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-29/\n DTEND;TZID=America/New_York:20260330T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260330T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260330T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-30/\n DTEND;TZID=America/New_York:20260406T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260406T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260406T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-31/\n DTEND;TZID=America/New_York:20260413T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260413T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260413T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-32/\n DTEND;TZID=America/New_York:20260420T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260420T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260420T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-33/\n DTEND;TZID=America/New_York:20260427T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260427T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260427T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-34/\n DTEND;TZID=America/New_York:20260504T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260504T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260504T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-35/\n DTEND;TZID=America/New_York:20260511T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260511T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260511T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-36/\n DTEND;TZID=America/New_York:20260518T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260518T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260518T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-37/\n DTEND;TZID=America/New_York:20260525T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260525T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260525T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-38/\n DTEND;TZID=America/New_York:20260601T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260601T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260601T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-39/\n DTEND;TZID=America/New_York:20260608T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260608T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260608T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-40/\n DTEND;TZID=America/New_York:20260615T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260615T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260615T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-41/\n DTEND;TZID=America/New_York:20260622T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260622T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260622T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-42/\n DTEND;TZID=America/New_York:20260629T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260629T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260629T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-43/\n DTEND;TZID=America/New_York:20260706T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260706T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260706T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-44/\n DTEND;TZID=America/New_York:20260713T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260713T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260713T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-45/\n DTEND;TZID=America/New_York:20260720T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260720T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260720T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-46/\n DTEND;TZID=America/New_York:20260727T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260727T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260727T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-47/\n DTEND;TZID=America/New_York:20260803T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260803T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260803T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-48/\n DTEND;TZID=America/New_York:20260810T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260810T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260810T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-49/\n DTEND;TZID=America/New_York:20260817T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260817T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260817T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-50/\n DTEND;TZID=America/New_York:20260824T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260824T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260824T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-51/\n DTEND;TZID=America/New_York:20260831T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260831T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260831T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-52/\n DTEND;TZID=America/New_York:20260907T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260907T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260907T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/ event/nlpllm-interest-group-53/\n DTEND;TZID=America/New_York:20260914T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20260914T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RECURRENCE-ID;TZID=America/New_York:20260914T160000 SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:\nAdmission:\nFree\n DTEND;TZID=America/New_York:20250915T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250915T160000 LOCATION:Zoom: Passcode Required\, URL: https://yale.zoom.us/j/93599941969 RRULE:FREQ=WEEKLY;UNTIL=20260915T035959Z;BYDAY=MO SEQUENCE:0 STATUS:Confirmed SUMMARY:NLP/LLM Interest Group UID:10f38bf8-dde0-4ad2-82d7-c6c1131308be END:VEVENT BEGIN:VEVENT DESCRIPTION:NOTE: BIS 525 students are required to attend in person. Other s are invited to attend in person\, but may also attend via Zoom. SPEAKER : Brian Tom\, PhD\, George S. Saden Visiting Scholar at Yale and Program me Leader and MRC Investigator\, MRC Biostatistics Unit\, University of C ambridge TITLE : “Understanding the impact of treatment in psoriatic arth ritis in the presence of selection bias and time varying confounding" ABS TRACT: Psoriatic arthritis is an inflammatory arthritis affecting the joi nts and skin. There is evidence to suggest that disease activity (i.e.\, swelling and pain) in the joints can lead to irreversible joint damage in the hands. Moreover\, these disease processes (disease activity and dama ge)\, alongside the skin aspect of the disease\, have an impact on the fu nctional ability and quality of life of patients. It is therefore importa nt to treat promptly and appropriately to reduce the risk of progression to damage and to improve the quality of life and activities of daily livi ng of patients. However\, assessing the impact of treatments on outcomes in psoriatic arthritis is not straightforward\, as the various treatments all work through reducing disease activity\, and disease activity influe nces both the timing and treatment received and the outcome over time. Ad ditionally\, although patients attending the Toronto Psoriatic Arthritis Clinic\, are supposed to be reviewed at regular intervals according to a standard protocol\, this does not necessarily happen. We demonstrate the importance of appropriately adjusting for confounding and selection bias and taking account of the observation process when answering the causal q uestion of whether there is an effect of percentage of time spent on dise ase modifying drugs on the time to first damage at any joint in the hands of patients with Psoriatic Arthritis. YSPH values inclusion and access f or all participants. If you have questions about accessibility or would l ike to request an accommodation\, please contact Charmila Fernandes at Ch armila.fernandes@yale.edu . We will try to provide accommodations request ed by September 11\, 2025.\n\nSpeaker:\nBrian Tom\, PhD\n\nAdmission:\nFr ee\n\nDetails URL:\nhttps://medicine.yale.edu/event/ysph-biostatistics-se minar-tba-9-16-25-copy-copy/\n DTEND;TZID=America/New_York:20250916T125000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250916T120000 GEO:41.302961;-72.931638 LOCATION:106-A&B\, 47 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:YSPH Biostatistics Seminar: “Understanding the impact of treatment in psoriatic arthritis in the presence of selection bias and time varyin g confounding" UID:067c48d8-07ec-45ea-80b2-f92fbb614bf5 END:VEVENT BEGIN:VEVENT DESCRIPTION:An Update on Systemic Therapy for Psoriasis and Atopic Dermati tis\n\nSpeaker:\nJeffrey Cohen\n\nAdmission:\nFree\n\nDetails URL:\nhttps ://medicine.yale.edu/event/general-internal-medicine-grand-rounds-an-upda te-on-systemic-therapy-for-psoriasis-atopic-dermatitis/\n DTEND;TZID=America/New_York:20250918T083000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250918T073000 SEQUENCE:0 STATUS:Confirmed SUMMARY:General Internal Medicine Grand Rounds\, An Update on Systemic The rapy for Psoriasis & Atopic Dermatitis UID:be7e215e-e7e9-43c2-9c1c-7468b786d0da END:VEVENT BEGIN:VEVENT DESCRIPTION:Psychiatry has long lacked objective\, quantitative measures c omparable to those in other areas of medicine. Neurobiological assays are inconsistent\, while clinical observation—though nuanced—remains subject ive and hard to scale. The rise of pervasive computing and digital sensin g now makes it possible to capture continuous behavioral\, cognitive\, an d contextual data in daily life. These multimodal streams\, analyzed with informatics and machine learning\, enable dynamic phenotypes of serious mental illness that move beyond static diagnoses toward precision\, perso nalization\, and closed-loop care. This talk will highlight recent effort s integrating mobile sensing\, digital phenotyping\, and single-case expe rimental designs in individuals with schizophrenia and bipolar disorder. Dr. Baker will discuss strategies for linking behavior to illness traject ories\, challenges in inference and generalizability\, and opportunities to connect digital phenotypes with neural circuits and treatment delivery —advancing psychiatry toward a more data-driven and mechanistically infor med science. Justin T. Baker\, MD\, PhD \, is the scientific director of the McLean Institute for Technology in Psychiatry (ITP) and director of t he Laboratory for Functional Neuroimaging and Bioinformatics at McLean Ho spital. He is also an associate professor of psychiatry at Harvard Medica l School. Dr. Baker’s research uses both large-scale studies and deep\, m ultilevel phenotyping approaches to understand the nature and underlying biology of mental illnesses. He is a clinical psychiatrist with expertise in schizophrenia and bipolar spectrum disorders and other disorders of e merging adulthood. In 2016\, Dr. Baker co-founded the ITP\, a first-of-it s-kind research and development center to foster tool development and nov el applications of consumer technology in psychiatric research and care d elivery.\n\nSpeaker:\nJustin Baker\, MD\, PhD\n\nAdmission:\nFree\n\nFood :\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu/event/bids-monthly-se minar-justin-baker/\n DTEND;TZID=America/New_York:20250918T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250918T120000 LOCATION:ZOOM: https://yale.zoom.us/j/95975389943 \, URL: https://yale.zoo m.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar UID:24a8fa0a-f2ee-445d-859e-4152f5773197 END:VEVENT BEGIN:VEVENT DESCRIPTION:\nSpeaker:\nLucila Ohno-Machado\n\nAdmission:\nFree\n\nFood:\n Refreshments served at 3:45 PM\n\nDetails URL:\nhttps://medicine.yale.edu /event/neurology-grand-rounds-lucila-ohno-machado-md-mba-phd/\n DTEND;TZID=America/New_York:20250924T170000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250924T160000 LOCATION:Join in person or virtually\, URL: https://yale.zoom.us/j/9351848 6899?pwd=t3f0e9dhsggxcCankaMtSLR4K6AZ1R.1 SEQUENCE:0 STATUS:Confirmed SUMMARY:Neurology Grand Rounds UID:e4599dc1-e654-418f-becf-73cd7f2224f9 END:VEVENT BEGIN:VEVENT DESCRIPTION:Abstract: Large Language Models are increasingly integrated in to scientific workflows and promise to transform discovery\, but progress depends on reliable ways to evaluate and interpret their capabilities. I n this talk\, I will present two complementary efforts on evaluating and understanding LLMs for science. First\, SciArena\, an open and collaborat ive platform for comparing LLMs on literature-grounded scientific tasks. SciArena provides a robust basis for assessing retrieval-augmented agents \, and its extension\, SciArena-Eval\, enables benchmarking of automated evaluation methods. Second\, I will discuss our study of scientific reaso ning\, where we investigate the roles of knowledge and reasoning using a new probing framework\, KRUX. Our analysis highlights distinct bottleneck s: retrieving task-relevant knowledge from model parameters and the need for explicit reasoning to surface domain insights. Together\, these works reveal key limitations of current models\, such as bottlenecks in retrie ving task-relevant knowledge and the importance of explicit reasoning for surfacing domain insights. We conclude with lessons learned from combini ng large-scale open evaluation with fine-grained probing\, and outline op portunities for building the next generation of trustworthy scientific LL Ms. Arman Cohan\, PhD is an Assistant Professor of Computer Science at Ya le University. His research interests are in large language models\, natu ral language processing and machine learning\, with a focus on understand ing\, evaluating\, and interpreting large language models.He is also inte rested in developing techniques to enhance LLM capabilities for complex a nd long-tail phenomena\, especially with the goal of making robust and ad aptable LLM systems that can address challenging real-world scenarios.\n\ nSpeaker:\nArman Cohan\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medic ine.yale.edu/event/ai-in-medicine-seminar-series-armancohan/\n DTEND;TZID=America/New_York:20250925T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250925T120000 LOCATION:Zoom: \, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:AI in Medicine Seminar Series UID:f1dfe7c9-115c-477e-9eb6-5e782406cd8e END:VEVENT BEGIN:VEVENT DESCRIPTION:NOTE: BIS 525 students are required to attend in person. Other s are invited to attend in person\, but may also attend via Zoom. SPEAKER : Brian Coleman\, DC\, MHS - Assistant Professor of Emergency Medicine\, Biomedical Informatics and Data Science\, and Biostatistics (Health Info rmatics)\, Yale University TITLE : “Bridging the Gap: From Unstructured C linic Notes to Standardized Outcomes Data in Veterans Health Administrati on Pain Care" ABSTRACT: Chronic pain disproportionately affects US Milita ry Veterans compared to the general US population. An important marker of high-quality care for chronic pain is the use of patient reported outcom e measures that can provide standardized data showing pre-\, intra-\, or post-treatment outcomes for clinical decision making. A substantial chall enge in the Veterans Health Administration (VHA) is the inconsistent coll ection of patient reported outcome measure data and its embedding within unstructured notes in the legacy electronic health record when documented . This presentation will highlight two efforts related to patient reporte d outcome measures data in VHA pain care. The first describes a retrospec tive analysis of clinic documentation from VHA chiropractic clinics using natural language processing to quantify patient reported outcome measure use as a quality metric. The second describes the implementation of a pa in measure set in pain clinics and interdisciplinary pain management team s across the VHA enterprise\, highlighting an implementation strategy pac kage with analysis of pain-related outcomes. YSPH values inclusion and ac cess for all participants. If you have questions about accessibility or w ould like to request an accommodation\, please contact Charmila Fernandes at Charmila.fernandes@yale.edu . We will try to provide accommodations r equested by September 25\, 2025.\n\nSpeaker:\nBrian Coleman\n\nAdmission: \nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/ysph-biostatistic s-seminar-tba-9-30-25-copy/\n DTEND;TZID=America/New_York:20250930T125000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20250930T120000 GEO:41.302961;-72.931638 LOCATION:106-A&B\, 47 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:YSPH Biostatistics Seminar: “Bridging the Gap: From Unstructured C linic Notes to Standardized Outcomes Data in Veterans Health Administrati on Pain Care" UID:241fa2f1-1e99-48eb-9697-1c53293fc97d END:VEVENT BEGIN:VEVENT DESCRIPTION:This a monthly webinar provided by YNHHS Epic Clinician Builde rs to help clinicians become more efficient and proficient in the use of our Epic electronic health record.\n\nSpeaker:\nRitche Hao\n\nAdmission:\ nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/making-epic-easier -webinar-haiku/\n DTEND;TZID=America/New_York:20251002T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251002T121500 LOCATION:We will meet on Zoom. The password is 812090.\, URL: https://ynhh .zoom.us/j/95945390228?pwd=bnU0YW5QL1VJVVVCN1BCVkpldkVCZz09 SEQUENCE:0 STATUS:Confirmed SUMMARY:Making Epic Easier Webinar - Haiku UID:50e61243-c0e9-4bc4-ab11-8133b5006eea END:VEVENT BEGIN:VEVENT DESCRIPTION:\nSpeakers:\nAmisha Dave\; Qingyu Chen\n\nAdmission:\nFree\n\n Details URL:\nhttps://medicine.yale.edu/event/yec-grand-rounds-case-prese ntations-101025/\n DTEND;TZID=America/New_York:20251010T081500 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251010T070000 SEQUENCE:0 STATUS:Confirmed SUMMARY:YEC Grand Rounds Case Presentations UID:01c1b332-7fb1-4a78-ac56-5c7fac778d0e END:VEVENT BEGIN:VEVENT DESCRIPTION:Hua Xu\, PhD\, will lead an information session on the Master of Science in Computational Biology and Biomedical Informatics (CBB) . Th e session is open to all prospective applicants interested in learning mo re about the program. The CBB master’s program is designed for both clini cians seeking a problem-solving edge and technical specialists aiming to expand their understanding of clinical practice. Students develop advance d research skills through coursework and structured research opportunitie s\, collaborating with faculty and practicing clinicians to create real-w orld\, publishable solutions.\n\nSpeaker:\nHua Xu\n\nAdmission:\nFree\n\n Details URL:\nhttps://medicine.yale.edu/event/cbb-ms-program-information- session-1/\n DTEND;TZID=America/New_York:20251020T210000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251020T200000 LOCATION:Zoom details will be provided after RSVP. SEQUENCE:0 STATUS:Confirmed SUMMARY:CBB MS Program Information Session UID:e35f7c6f-1c58-411a-83b8-fe4117fbb9fc END:VEVENT BEGIN:VEVENT DESCRIPTION:Please join us for a dean's workshop introducing the Yale Biom edical Imaging Institute (Yale BioImaging)\, led by Director Georges El F akhri\, PhD. The workshop\, titled "Yale Biomedical Imaging Institute: Ad vancing the Understanding of Health & Guiding Treatment \," will be held on Tuesday\, Oct. 21\, from 1 - 6 p.m. The mission of Yale BioImaging is to cultivate an interdisciplinary and dynamic research environment that w ill transform our understanding of health and disease through biomedical imaging. The workshop highlights the work of scientists and clinicians ac ross the university that are employing advanced biomedical imaging techno logies and translating them in a variety of fields such as brain\, heart\ , cancer\, image-guided therapy\, and data sciences. The workshop also fe atures a roundtable discussion by leaders of imaging-intensive department s to identify strategic opportunities for innovation and impact. This hyb rid event\, hosted by the School of Medicine dean’s office\, will take pl ace in person in The Anlyan Center auditorium\, N107 (300 Cedar Street) a nd via Zoom . Those interested in presenting a poster at the workshop may submit an abstract here by Oct. 3. YALE BIOMEDICAL IMAGING INSTITUTE: AD VANCING THE UNDERSTANDING OF HEALTH & GUIDING TREATMENT WELCOME\, 1 - 1:0 5 PM Nancy J. Brown\, MD\, Jean and David W. Wallace Dean of Medicine and C.N.H. Long Professor of Internal Medicine\, Yale School of Medicine INS TITUTE OVERVIEW\, 1:05 - 1:20 PM Georges El Fakhri\, PhD\, Elizabeth Mear s and House Jameson Professor of Radiology & Biomedical Imaging\, Therape utic Radiology and of Biomedical Informatics & Data Science\; Director\, Yale Biomedical Imaging Institute\; and Director\, PET Center IMAGING TEC HNOLOGY\, 1:20 - 1:40 PM POSITRON EMISSION TOMOGRAPHY TECHNOLOGIES AND CA PABILITIES AT YALE Marc D. Normandin\, PhD\, Associate Professor of Radio logy & Biomedical Imaging\; and Director\, Yale PET Core MAGNETIC RESONAN CE TECHNOLOGIES AND CAPABILITIES AT YALE Henk De Feyter\, PhD\, Associate Professor of Radiology & Biomedical Imaging IMAGING TRANSLATION\, 1:40- 2:00 PM IMAGING VULNERABILITY IN NEURODEGENERATION Carolyn Fredericks\, M D\, Assistant Professor of Neurology and Henry F. McCance Scholar in Neur odegeneration THERANOSTICS: TRANSLATING IMAGING TO THERAPY IN CANCER Pame la L. Kunz\, MD\, Professor of Internal Medicine (Medical Oncology)\; Dir ector\, Center for Gastrointestinal Cancers at Smilow Cancer Hospital and Yale Cancer Center\; and Chief\, GI Medical Oncology IMAGING DATA SCIENC ES\, 2:00 - 2:20 PM INFRASTRUCTURE AND APPLICATIONS IN IMAGE-GUIDED RADIA TION ONCOLOGY\, BREAST\, AND PROSTATE IMAGING Thibault Marin\, PhD\, Assi stant Professor of Radiology & Biomedical Imaging and of Biomedical Infor matics & Data Science John Onofrey\, PhD\, Assistant Professor of Radiolo gy & Biomedical Imaging\, of Urology\, and of Biomedical Engineering Nich a Dvornek\, PhD\, Assistant Professor of Radiology & Biomedical Imaging a nd of Biomedical Engineering QUESTIONS & ANSWERS\, 2:20 - 2:30 PM NETWORK ING BREAK\, 2:30 - 2:45 PM IMAGING SUCCESS STORIES\, 2:45 - 3:15 PM USING PET TO UNDERSTAND NEUROIMMUNE-RELATED BRAIN HEALTH Kelly Cosgrove\, PhD\ , Charles B.G. Murphy Professor of Psychiatry\, of Neuroscience\, and of Radiology & Biomedical Imaging YALE TRANSLATIONAL RESEARCH IMAGING CENTER (Y-TRIC): MULTI-MODALITY AND MOLECULAR IMAGING AND IMAGE-GUIDED INTERVEN TIONS Albert Sinusas\, MD\, Professor of Medicine (Cardiology)\, of Radio logy & Biomedical Imaging\, and of Biomedical Engineering\; and Director\ , Yale Translational Research Imaging Center (Y-TRIC) ROUNDTABLE WITH CHA IRS OF IMAGING-INTENSIVE DEPARTMENTS\, 3:15 - 4:15 PM Jeffrey Brock\, PhD \, William S. Massey Professor of Mathematics\; Professor of Statistics & Data Science\; and Dean\, School of Engineering & Applied Science Peter M. Glazer\, MD\, PhD\, Robert E. Hunter Professor of Therapeutic Radiolog y and Professor of Genetics\; and Chair\, Therapeutic Radiology Wolfram G oessling\, MD\, PhD\, Ensign Professor of Medicine and Professor of Cellu lar and Molecular Physiology\; and Chair of Internal Medicine Pooja Khatr i\, MD\, MS\, Albert E Kent Professor and Chair of Neurology John Krystal \, MD\, Robert L. McNeil\, Jr. Professor of Translational Research\; Prof essor of Psychiatry\, of Neuroscience\, and of Psychology\; Chair of Psyc hiatry\; and Co-Director\, YCCI Lucila Ohno-Machado\, MD\, MBA\, PhD\, Wa ldemar von Zedtwitz Professor of Medicine and Biomedical Informatics & Da ta Science\; Deputy Dean for Biomedical Informatics\; Chair\, Department of Biomedical Informatics & Data Science\; and Co-Director\, YCCI Christo pher Whitlow\, MD\, PhD\, MHA\, incoming Chair of the Department of Radio logy & Biomedical Imaging and Assistant Dean for Translational Research E ric Winer\, MD\, Alfred Gilman Professor of Pharmacology and Professor of Medicine (Medical Oncology)\; Deputy Dean for Cancer Research\; Director \, Yale Cancer Center\; and President and Physician-in-Chief\, Smilow Can cer Hospital WHAT CAN THE INSTITUTE DO FOR YOU? 4:15 - 4:25 PM Georges El Fakhri\, PhD CLOSING REMARKS\, 4:25 - 4:30 PM Nancy J. Brown\, MD POSTER SESSION WITH REFRESHMENTS\, 4:30 - 6:00 PM The workshop is being recorde d and will be available online after the event at https://medicine.yale.e du/about/deanoffice/workshop/ . Dean’s Workshop Contact: beth.pranger@yal e.edu Please click the link below to join the webinar: https://yale.zoom. us/j/93075443840 Link available DAY OF WORKSHOP at 12:30 PM.\n\nSpeakers: \nNancy Brown\; Georges El Fakhri\; Marc Normandin\; Henk De Feyter\; Pam ela Kunz\; Carolyn Fredericks\; Nicha Dvornek\; Thibault Marin\; John Ono frey\; Kelly Cosgrove\; Albert Sinusas\; Jeffrey Brock\; Peter Glazer\; W olfram Goessling\; Pooja Khatri\; John Krystal\; Lucila Ohno-Machado\; Ch ristopher Whitlow\, MD\, PhD\, MHA\; Eric Winer\n\nAdmission:\nFree\n\nDe tails URL:\nhttps://medicine.yale.edu/event/deans-workshop-bioimaging-oct -21/\n DTEND;TZID=America/New_York:20251021T180000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251021T130000 LOCATION:URL: https://yale.zoom.us/j/93614615801 SEQUENCE:0 STATUS:Confirmed SUMMARY:Dean's Workshop: "Yale Biomedical Imaging Institute: Advancing the Understanding of Health & Guiding Treatment" UID:a5c87bba-04b7-4859-9eb7-f662e8576330 END:VEVENT BEGIN:VEVENT DESCRIPTION:CBB PhD Open House Tuesday\, October 21\, 8:00 PM – 9:00 PM\, via Zoom (link to be shared upon registration) Virtual open house session for interested applicants to learn more about Yale’s Computational Biolo gy and Biomedical Informatics (CBB) combined program in the Biological an d Biomedical Sciences (BBS). This is a great opportunity to learn about t he PhD graduate program\, ask questions regarding the application process \, and meet with the Directors of Graduate Studies and Admissions for CBB . Please register for the event here .\n\nSpeakers:\nSteven Kleinstein\; Corey O'Hern\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.e du/event/cbb-phd-open-house/\n DTEND;TZID=America/New_York:20251021T210000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251021T200000 LOCATION:Zoom (link to be shared upon registration) SEQUENCE:0 STATUS:Confirmed SUMMARY:CBB PhD Virtual Open House UID:6749d1c5-e90d-4974-9d6f-f803a5f6c833 END:VEVENT BEGIN:VEVENT DESCRIPTION:This session will examine current threats to public health res earch funding\, the impact of recent federal policies on YSPH faculty res earch\, and collective strategies to push back against these actions.\n\n Speakers:\nChelsey Carter\; John Pachankis\; Terika McCall\; Sunil Parikh \n\nAdmission:\nFree\n\nFood:\nLunch: A Pizza lunch will be provided afte r the session.\n\nDetails URL:\nhttps://medicine.yale.edu/event/ysph-sbs- 525-seminar-series-oct-28-2025/\n DTEND;TZID=America/New_York:20251028T125000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251028T120000 GEO:41.303666;-72.932218 LOCATION:Yale School of Public Health (LEPH)\, Winslow Auditorium\, 60 Col lege Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:YSPH-SBS 525 Seminar: Teach-in Series "Threats to Public Health Re search Funding" UID:3c84e9bc-981c-4773-9f20-c7ecd31d9fbb END:VEVENT BEGIN:VEVENT DESCRIPTION:Corey O'Hern\, PhD\, will lead an information session on the M aster of Science in Computational Biology and Biomedical Informatics (CBB ) . The session is open to all prospective applicants interested in learn ing more about the program. The CBB master’s program is designed for both clinicians seeking a problem-solving edge and technical specialists aimi ng to expand their understanding of clinical practice. Students develop a dvanced research skills through coursework and structured research opport unities\, collaborating with faculty and practicing clinicians to create real-world\, publishable solutions.\n\nSpeaker:\nCorey O'Hern\n\nAdmissio n:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/cbb-ms-program- information-session-2/\n DTEND;TZID=America/New_York:20251029T093000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251029T083000 LOCATION:Zoom details will be provided after RSVP. SEQUENCE:0 STATUS:Confirmed SUMMARY:CBB MS Program Information Session UID:5fcab198-6d42-49b2-8f23-439ba82dd32a END:VEVENT BEGIN:VEVENT DESCRIPTION:The CSEI chalk talk series consists of speakers presenting on the general principles they are employing in their research and how their methods are being (could be) applied to investigate systems and engineer ing immunological areas of interest. Presenters use the chalk board only (no slides) to share their work and ideas with the audience. Presenters a re asked to focus on their perspectives and opinions within their area of interest\, as well as introduce their work in progress and avenues they would be excited to pursue in the future. The audience is encouraged to a sk questions during the presentation\, as the chalk talk format is intend ed to spark questions and dynamic discussion. The audience will be divers e\, with participants expected from Immunobiology\, Computational Biology \, Biomedical Engineering\, Molecular and Cellular Biology\, Mathematics and Data Science.\n\nSpeaker:\nKathryn Miller-Jensen\n\nAdmission:\nFree\ n\nDetails URL:\nhttps://medicine.yale.edu/event/kathryn-miller-jensen-gi ves-csei-chalk-talk/\n DTEND;TZID=America/New_York:20251029T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251029T120000 GEO:41.304215;-72.931754 LOCATION:1116\, 100 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:Kathryn Miller-Jensen gives CSEI Chalk Talk UID:6b7d2b6c-9171-476f-8766-d193a3eaf070 END:VEVENT BEGIN:VEVENT DESCRIPTION:IN PERSON EVENT REGISTRATION REQUIRED by 10/21/25 REGISTRATION LINK : https://forms.gle/jeEYDvWKzoeQ4Fce7 Reception: 4:00 – 5:00 \, Med ical Historical Library Duffy Lecture: 5:30 – 7:00 PM \, Harkness Auditor ium LOCATION: Harvey Cushing/John Hay Whitney Medical Library\, 333 Cedar Street\, New Haven Zoom link: https://yale.zoom.us/webinar/register/WN_1 wuEIsrqSTe6h1rcWSAo1g\n\nSpeaker:\nMildred Cho\, PhD\n\nAdmission:\nFree\ n\nFood:\nCocktails\, Dinner\n\nDetails URL:\nhttps://medicine.yale.edu/e vent/annual-thomas-p-duffy-memorial-lecture-in-medical-ethics-topic-ai-et hics/\n DTEND;TZID=America/New_York:20251029T190000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251029T173000 LOCATION:IN PERSON EVENT REGISTRATION REQUIRED by 10/17/25\nREGISTRATION L INK: https://forms.gle/jeEYDvWKzoeQ4Fce7\n\nReception: 4:00 – 5:00\, Medi cal Historical Library\nDuffy Lecture: 5:30 – 7:00 PM\, Harkness Auditori um\nLOCATION: Harvey Cushing/John Hay Whitney Medical Library\, 333 Cedar Street\, New Haven\nZoom link: https://yale.zoom.us/webinar/register/WN_ 1wuEIsrqSTe6h1rcWSAo1g\n SEQUENCE:0 STATUS:Confirmed SUMMARY:Program for Biomedical Ethics: Annual Thomas P. Duffy Memorial Lec ture in Medical Ethics UID:0deea5b9-f936-42a6-8cfa-0b600cfae0e8 END:VEVENT BEGIN:VEVENT DESCRIPTION:For those unable to attend in person\, please join us on Zoom! Zoom link: https://yale.zoom.us/j/98011069478 Password: Available on out look calendar invite and weekly meeting announcement\n\nSpeaker:\nChristo pher Cai\, MD\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale. edu/event/yale-gim-research-in-progress-meeting-iii/\n DTEND;TZID=America/New_York:20251030T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251030T120000 GEO:41.302200;-72.933362 LOCATION:Hope Memorial Building\, H216\, 315 Cedar Street\, New Haven\, CT \, United States SEQUENCE:0 STATUS:Cancelled SUMMARY:Yale GIM Research in Progress Meeting UID:c5380791-790b-4bfa-af1d-434493e4dfc5 END:VEVENT BEGIN:VEVENT DESCRIPTION:Meaning and Nature of Physician Work in the World of AI: Is th e Fundamental Theorem of Informatics Dead? This presentation will examine the modern relevance of the Fundamental Theorem of Informatics\, which p osits that a human partnered with an information resource is superior to the human working alone. David Rosenthal\, MD\, will explore whether the current state of the human-computer interface in medicine—dominated by co mplex electronic health records and emerging AI—still upholds this princi ple. The talk will question if these systems truly augment clinical intel ligence or have devolved into sources of cognitive friction and burnout. What is the future work of physicians?\n\nSpeaker:\nDavid Rosenthal\n\nAd mission:\nFree\n\nFood:\nLunch\n\nDetails URL:\nhttps://medicine.yale.edu /event/ai-in-medicine-or-student-interest-group-seminar/\n DTEND;TZID=America/New_York:20251030T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251030T120000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:AI in Medicine | Student Interest Group Seminar UID:7d19f3e6-0a58-4c6d-aaa8-18c350c99661 END:VEVENT BEGIN:VEVENT DESCRIPTION:This program will highlight awareness in diagnosis and treatme nt for patients with neuroendocrine tumors.\n\nSpeakers:\nPamela Kunz\; D avid Klimstra\; Georges El Fakhri\n\nAdmission:\nFree\n\nDetails URL:\nht tps://medicine.yale.edu/event/smilow-shares-nets-awareness-day-2025/\n DTEND;TZID=America/New_York:20251110T193000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251110T183000 LOCATION:Register by Zoom\, URL: https://yale.zoom.us/webinar/register/WN_ MXw4RU9wSh2rHRo3t7fDew SEQUENCE:0 STATUS:Confirmed SUMMARY:Smilow Shares UID:1aad185c-2a4a-4c94-9ee4-fd7cb744361e END:VEVENT BEGIN:VEVENT DESCRIPTION:CBB PhD Open House Tuesday\, November 11\, 8:00 PM – 9:00 PM\, via Zoom (link to be shared upon registration) Virtual open house sessio n for interested applicants to learn more about Yale’s Computational Biol ogy and Biomedical Informatics (CBB) combined program in the Biological a nd Biomedical Sciences (BBS). This is a great opportunity to learn about the PhD graduate program\, ask questions regarding the application proces s\, and meet with the Directors of Graduate Studies and Admissions for CB B. Please register for the event here .\n\nSpeakers:\nSteven Kleinstein\; Corey O'Hern\n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale. edu/event/cbb-phd-virtual-open-house-nov-11/\n DTEND;TZID=America/New_York:20251111T210000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251111T200000 LOCATION:Zoom (link to be shared upon registration) SEQUENCE:0 STATUS:Confirmed SUMMARY:CBB PhD Virtual Open House UID:30b53c82-14c4-4d1c-b5a9-f7b65bb1b72e END:VEVENT BEGIN:VEVENT DESCRIPTION:The CSEI chalk talk series consists of speakers presenting on the general principles they are employing in their research and how their methods are being (could be) applied to investigate systems and engineer ing immunological areas of interest. Presenters use the chalk board only (no slides) to share their work and ideas with the audience. Presenters a re asked to focus on their perspectives and opinions within their area of interest\, as well as introduce their work in progress and avenues they would be excited to pursue in the future. The audience is encouraged to a sk questions during the presentation\, as the chalk talk format is intend ed to spark questions and dynamic discussion. The audience will be divers e\, with participants expected from Immunobiology\, Computational Biology \, Biomedical Engineering\, Molecular and Cellular Biology\, Mathematics and Data Science.\n\nSpeaker:\nAndrew Martins\n\nAdmission:\nFree\n\nDeta ils URL:\nhttps://medicine.yale.edu/event/andrew-martins-gives-csei-chalk -talk/\n DTEND;TZID=America/New_York:20251112T130000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251112T120000 GEO:41.304215;-72.931754 LOCATION:1116\, 100 College Street\, New Haven\, CT\, United States SEQUENCE:0 STATUS:Confirmed SUMMARY:CSEI Chalk Talk UID:13e47edb-7b3c-4641-b0d2-9830ae2347a5 END:VEVENT BEGIN:VEVENT DESCRIPTION:Traditional clinical prediction models are narrowly focused on outcomes like length of stay\, readmission\, or disease progression. Bui lding and maintaining these single-purpose models demands substantial dat a and feature engineering\, limiting scalability and generalization acros s health systems. Developed by Epic in collaboration with researchers at Yale University and Microsoft Research\, Curiosity is a family of foundat ion models for longitudinal health records designed to support a diverse set of clinical tasks within a single generative modeling approach. Train ed on de-identified data from 118 million patients and 115 billion clinic al events from hundreds of healthcare systems in Cosmos\, Curiosity model s patient timelines as sequences of medical events\, enabling prediction and simulation of clinical trajectories. Davis White will outline the met hodological framework underlying the first version of Curiosity\, includi ng the establishment of scaling laws that relate data volume\, model capa city\, and performance in medical event modeling. Results across 78 real- world clinical and operational tasks demonstrate that Curiosity can match or exceed specialized models without task-specific tuning. These finding s suggest that foundation models can support more generalizable\, scalabl e\, and data-driven approaches to clinical prediction and research.\n\nSp eaker:\nDavis White\n\nAdmission:\nFree\n\nFood:\n\n\nDetails URL:\nhttps ://medicine.yale.edu/event/bids-special-seminar-epic/\n DTEND;TZID=America/New_York:20251113T110000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251113T100000 LOCATION:Zoom \nMeeting ID: 954 9953 6191\, URL: https://yale.zoom.us/j/9 5499536191 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Special Seminar UID:bb4b4b7c-d086-4ab4-8dc6-f38e51aa6d6c END:VEVENT BEGIN:VEVENT DESCRIPTION:Discover the Medical Software and Medical AI program offered b y Yale’s Biomedical Informatics and Data Science department. This fully o nline program is currently accepting applications and will begin in Janua ry 2025.In this session\, you’ll gain insights into the program’s curricu lum and have the opportunity to ask questions during the dedicated Q&A se gment. Don’t miss this chance to advance your career in the rapidly evolv ing field of healthcare technology! Learn More: https://online.yale.edu/m edical-software-ai-program\n\nSpeaker:\nXenophon Papademetris\n\nAdmissio n:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/yale-certificat e-program-in-medical-software-and-medical-ai-information-session/\n DTEND;TZID=America/New_York:20251113T210000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251113T200000 LOCATION:Zoom \, URL: https://yale.zoom.us/j/98933464530 SEQUENCE:0 STATUS:Confirmed SUMMARY:Yale Certificate Program in Medical Software and Medical AI Inform ation session UID:017be452-0abc-4313-a672-c23c48c52d54 END:VEVENT BEGIN:VEVENT DESCRIPTION:Corey O'Hern\, PhD\, will lead an information session on the M aster of Science in Computational Biology and Biomedical Informatics (CBB ). The session is open to all prospective applicants interested in learni ng more about the program. The CBB master’s program is designed for both clinicians seeking a problem-solving edge and technical specialists aimin g to expand their understanding of clinical practice. Students develop ad vanced research skills through coursework and structured research opportu nities\, collaborating with faculty and practicing clinicians to create r eal-world\, publishable solutions.\n\nSpeaker:\nCorey O'Hern\n\nAdmission :\nFree\n\nFood:\n\n\nDetails URL:\nhttps://medicine.yale.edu/event/cbb-m s-program-information-session-3/\n DTEND;TZID=America/New_York:20251118T210000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251118T200000 LOCATION:Join via Zoom\nMeeting ID: 944 4273 8119\, URL: https://yale.zoom .us/j/94442738119 SEQUENCE:0 STATUS:Confirmed SUMMARY:CBB MS Program Information Session UID:99e06d46-9887-49bf-8adb-d9dc9ecdcf96 END:VEVENT BEGIN:VEVENT DESCRIPTION:Modeling Immune Recognition with Language and Structural Model s: New Directions in Computational Proteomics Recent advances in computat ional proteomics are opening new avenues to understand how the immune sys tem recognizes and responds to disease. María Rodríguez Martínez\, PhD\, will present her group's work on modeling immune receptor binding—specifi cally\, how T cell receptors (TCRs) and B cell receptors (antibodies) eng age with their targets. She will discuss sequence-based approaches\, incl uding fine-tuning protein language models for calibrated receptor binding predictions and ensemble methods to identify autoreactive T cell recepto rs with applications in autoimmune disease. She will then cover structure -based modeling\, describing how her team combines structural predictions with graph-based methods to rank antibody binders\, models TCR flexibili ty using generative AI trained on molecular dynamics simulations\, and in tegrates confidence scores. with energetic and geometric criteria to asse ss interaction reliability.\n\nSpeaker:\nMaría Rodríguez Martínez\n\nAdmi ssion:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/bids-monthl y-seminar-1120/\n DTEND;TZID=America/New_York:20251120T120000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251120T110000 LOCATION:Zoom\, URL: https://yale.zoom.us/j/95975389943 SEQUENCE:0 STATUS:Confirmed SUMMARY:BIDS Monthly Seminar UID:60be3e36-323a-47ba-8176-45456f4a6fe9 END:VEVENT BEGIN:VEVENT DESCRIPTION:About the Talk Join Maxwell Salvatore\, PhD\, MPH\, Postdoctor al Fellow at the University of Pennsylvania\, for a hands-on tutorial exp loring how to leverage the NIH All of Us Research Program data for biomed ical and public health research. Dr. Salvatore will demonstrate approache s for studying the risks\, benefits\, and pharmacogenomics of GLP-1 recep tor agonists (RAs) using electronic health records (EHR) and EHR-linked b iobank data. This session is ideal for researchers and students intereste d in learning how to navigate\, analyze\, and apply large-scale health da tasets in precision medicine and population health.About the Speaker Dr. Maxwell Salvatore is a Postdoctoral Fellow working with Dr. Yong Chen in the Department of Biostatistics\, Epidemiology\, and Informatics and Dr. Marylyn Ritchie in the Department of Genetics at the University of Pennsy lvania. His work focuses on developing principled methods for analyzing e lectronic health record–linked biobanks and making these tools more acces sible to researchers. His research has spanned topics including COVID-19\ , digestive cancers\, diabetes\, and obesity\, with an emphasis on precis ion medicine and health equity.\n\nAdmission:\nFree\n\nFood:\nSnacks\n\nD etails URL:\nhttps://medicine.yale.edu/event/lets-talk-data-nih-tutorial- nov-2025/\n DTEND;TZID=America/New_York:20251121T110000 DTSTAMP:20260305T150913Z DTSTART;TZID=America/New_York:20251121T093000 LOCATION:URL: https://yale.zoom.us/meeting/register/X_QmIRXnRyC72yk-XQFq3A SEQUENCE:0 STATUS:Confirmed SUMMARY:Let's Talk Data: How to use the NIH All of Us Tutorial UID:7ebc1c40-c715-4b55-8037-f512d8c7b7a9 END:VEVENT END:VCALENDAR