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SUMMARY:A RAG-LLM Workflow for Observational Health Research - Jacob Zelko
 \, Param Thakkar
DTSTART;TZID=America/New_York:20250723T163000
DTEND;TZID=America/New_York:20250723T164000
DTSTAMP:20260809T010456Z
UID:pretalx-juliacon-2025-J9PJ9T@pretalx.com
DESCRIPTION:We describe a Retrieval-Augmented Generation (RAG)-informed La
 rge Language Model (LLM) workflow for querying observational health data i
 n the OMOP Common Data Model (OMOP CDM). Leveraging Julia software such as
  FunSQL.jl and OMOPCDMCohortCreator.jl\, we explore how the model can auto
 mate and refine complex research queries in health research settings. This
  work explores RAG architectures\, query examples\, and reproducibility wi
 thin health informatics.
LOCATION:Lawrence Room 104 - Function Room
URL:https://pretalx.com/juliacon-2025/talk/J9PJ9T/
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