A new multi-agent system called DIASENTINEL has been developed for on-premise screening of type 2 diabetes risk using electronic health records. This system aims to provide auditable and privacy-preserving clinical decision support by integrating risk prediction, clinical signal extraction, and verification against American Diabetes Association guidelines. The DIASENTINEL framework includes a dashboard for batch screening and an interface for generating patient reports with cited recommendations and verification results. AI
IMPACT This system demonstrates a practical approach to using LLMs for auditable and privacy-preserving clinical decision support in healthcare.
RANK_REASON The cluster describes a research paper published on arXiv detailing a new AI system for a specific medical application.
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