Agentic Discovery of Blood Biomarkers via Distilled Health Records

Researchers used a graph attention network trained on 5.4 million patient records to create a scoring tool for blood biomarker discovery. This allows LLM agents to propose candidates without accessing raw, private patient data, achieving a median 4.18 AUC increase over literature-based methods.