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In an op-ed published August 2 in the New England Journal of Medicine, four members of Yale's health ecosystem lay out a case for how to make America trust health experts again. One of the authors, Dr. Kristen Panthagani, MD, PhD, summarizes the article's key points in this 3 Essential Questions feature.

A new Yale study investigates how artificial intelligence might help identify patients at risk of developing agitation in the emergency department. 

For the fourth consecutive year, the Department of Emergency Medicine (DEM) at Yale School of Medicine has ranked #1 in the nation for National Institutes of Health (NIH) research funding, according to the Blue Ridge Institute for Medical Research.

A recent scoping review in Applied Clinical Informatics, titled "Interventions to Mitigate EHR and Documentation Burden in Health Professions Trainees, " presents a workflow model to support intervention development. Led by Deborah Levy, MD MPH MS, a Lecturer at Yale School of Medicine in BIDS, the work addresses the challenge faced when designing interventions to mitigate trainee EHR burden. This work was completed as part of Dr. Levy's Master's in Health and Clinical Informatics OHSU capstone project.

Yale BIDS welcomes Andrew Loza, Instructor of Biomedical Informatics and Data Science. Dr. Loza aims to improve patient care by developing statistical and deep learning methods that leverage comprehensive patient data.

BIDS has welcomed several new faculty, fellows, and staff to our team since October 2024.

Ted Melnick is not only a researcher at Yale University but a proud father of three. During his transition from medical school and residency, he ran marathons and competed in triathlons, which required him to balance three disciplines—running, biking, and swimming. This ability to focus on multiple areas manifests in his professional life, where he integrates emergency medicine, informatics, and public health to improve patient care.

Yale and Mila Researchers at NeurIPS present Trajectory Flow Matching (TFM), a scalable and stable method for training Neural SDEs that improves clinical time series modeling and uncertainty prediction.

Yale Emergency Medicine shone brightly at SAEM24, earning numerous awards and delivering over 50 diverse presentations, highlighting their significant contributions to academic emergency medicine.