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Abstract Number: 0033
VLRCHAT: A LARGE LANGUAGE MODEL CHATBOT THAT LEVERAGES RETRIEVAL-AUGMENTED GENERATION (RAG) TO ANSWER CLINICAL QUESTIONS
SHM Converge 2025
Background: We created a generative artificial intelligence chatbot (“VLRChat”) that draws from a comprehensive curricular resource (the 480-page Vanderbilt Housestaff Handbook) to answer point-of-care clinical questions by hospitalists and inpatient clinical teams. Time constraints and cognitive overload frequently prevent hospitalist faculty and learners from determining the optimal, most current answers to clinical questions: as many [...]
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