LLM-Match: An Open-Sourced Patient Matching Model Based on Large Language Models and Retrieval-Augmented Generation

Understand

Patient matching is the process of linking patients to appropriate clinical trials by accurately identifying and matching their medical records with trial eligibility criteria.

• We propose LLM-Match, a novel framework for patient matching leveraging fine-tuned open-source large language models.
• Our approach consists of four key components.
• First, a retrieval-augmented generation (RAG) module extracts relevant patient context from a vast pool of electronic health records (EHRs).