MedAI

Title: Large Language Models as Universal Medical Forecasters
Speaker: Zeljko Kraljevic
Abstract:
Electronic Health Records hold detailed longitudinal information about each patient's health status and general clinical history, a large portion of which is stored within the unstructured text. Existing approaches focus mostly on structured data or a subset of single-domain outcomes. We will explore how temporal modeling of patients from free text and structured data, using large language models fine tuned on over 1M million patient timelines can be used to forecast a wide range of future disorders, medications, procedures and symptoms.
Speaker Bio:
Zeljko Kraljevic is a researcher in AI for Healthcare at King’s College London working on temporal modeling of patients and disorders using generative transformers.
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