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DTSTART:20241103T020000
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DESCRIPTION:From Lab Values to Clinical Reasoning: Laboratory Test Interpr
 etation in the Era of Large Language Models by Balu Bhasuran\, PhD\, Rese
 arch Faculty in the School of Information\, College of Communication and 
 Information at Florida State University. Abstract: Large language models 
 (LLMs) are increasingly being used to interpret laboratory test results. 
 However\, laboratory test interpretation remains a complex clinical reaso
 ning task that requires more than reference-range knowledge alone. Accura
 te interpretation must integrate patient context\, longitudinal trends\, 
 clinical reasoning\, and an understanding of uncertainty. In this talk\, 
 Bhasuran will present a research program examining how LLMs interpret lab
 oratory tests across patient-facing\, diagnostic\, and reasoning-centered
  settings. He will begin with studies evaluating patient-facing LLM-gener
 ated explanations of laboratory results\, followed by the development of 
 benchmark datasets such as LabQAR and retrieval-augmented generation syst
 ems designed to improve contextual accuracy. He will then discuss how lab
 oratory results influence LLM-generated differential diagnosis\, the role
  of causal reasoning in laboratory test interpretation\, and recent work 
 using EHR-derived patient profiles to generate personalized Question Prom
 pt Lists. Together\, these studies motivate a future vision of safe\, ret
 rieval-grounded\, and clinician-supervised AI systems that empower patien
 ts and support clinical decision-making. Balu Bhasuran\, PhD\, is a Resea
 rch Faculty I in the School of Information\, College of Communication and
  Information\, at Florida State University. He previously served as a Vis
 iting Assistant Professor and Postdoctoral Fellow in the eHealth Lab at F
 lorida State University under the mentorship of Prof. Zhe He. Before join
 ing FSU\, he was a Postdoctoral Fellow at the Bakar Computational Health 
 Sciences Institute at the University of California\, San Francisco. Dr. B
 hasuran's research focuses on clinical natural language processing\, mach
 ine learning\, generative AI\, information extraction\, and clinical data
  science. Over the past decade\, he has developed classification and pred
 iction models using biomedical and clinical data for a range of applicati
 ons\, including early diagnosis of rare diseases\, disease severity class
 ification\, adverse drug event detection\, organ transplant rejection pre
 diction\, and medication adherence modeling. His broader research interes
 ts include causal inference\, literature-based discovery\, knowledge grap
 hs\, network visualization\, fairness\, and explainability in machine lea
 rning.\n\nSpeaker:\nBalu Bhasuran\, PhD\n\nAdmission:\nFree\n\nDetails UR
 L:\nhttps://medicine.yale.edu/event/ai-frontiers-seminar-7-20/\n
DTEND;TZID=America/New_York:20260720T170000
DTSTAMP:20261002T120932Z
DTSTART;TZID=America/New_York:20260720T160000
LOCATION:Join our mailing list to receive Zoom Link & Passcode: https://ma
 ilman.yale.edu/mailman/listinfo/nlp-llm-ig\n
SEQUENCE:0
STATUS:Confirmed
SUMMARY:🤖 AI Frontiers Seminar: Hosted by NLP/LLM Interest Group (Virtual
  Webinar)
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