Researchers present a lightweight retrieval-augmented generation (RAG) approach with large language models for efficient patient-trial matching. The method emphasizes computational efficiency while maintaining matching accuracy for clinical trial recruitment. This application demonstrates how modern NLP techniques can scale healthcare trial-matching operations.
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Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching
Lightweight RAG-LLM system scales patient-trial matching while cutting computational overhead, proving clinical recruitment can be automated without heavy infrastructure.
Monday, April 27, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.CL (Computation & Language)BY sys://pipeline
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