AIBullisharXiv – CS AI · Jun 196/10
🧠
Configurable Clinical Information Extraction with Agentic RAG: What Works, What Breaks, and Why
Researchers deployed ACIE, an on-premise agentic RAG system at University Medicine Essen, to extract clinical information from fragmented patient records spanning hundreds of documents. Clinicians validated 7,326 extractions with 96.5% acceptance rates, demonstrating that agentic architectures with explicit reasoning can overcome standard RAG failures in handling temporal dependencies and missing metadata in healthcare contexts.