FHIR Data and AI Integration Kit for Building Medical Information Systems
FHIR-AI-Hackathon-Kit Awaiting Review - Intersystems Open Exchange
Summary
This kit provides tutorials on developing advanced medical applications by integrating Electronic Health Record (FHIR) data with generative AI using Python. It enables the analysis of unstructured text, such as clinical notes and patient histories, through vector search and LLM processing to provide insights for healthcare professionals.
Details
This repository is a comprehensive tutorial set designed for building applications that combine FHIR data and Generative AI using InterSystems IRIS and Python. The key steps include setting up the FHIR server environment using Docker. Next, it demonstrates converting FHIR data into SQL tables using the FHIR-SQL Builder, allowing querying via Python. Crucially, it implements 'vector search' by taking clinical notes (DocumentReference) text, vectorizing them, and creating a new table within IRIS for rapid retrieval of related information. The final stage involves passing a prompt—which includes system instructions, relevant notes, and a user query—to a Large Language Model (LLM). This achieves a chatbot function that helps medical professionals quickly and comprehensively understand a patient's history. The kit offers a practical development model integrating multiple advanced technologies: FHIR data structuring, SQL querying, vector embedding, and RAG (Retrieval-Augmented Generation).
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