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AM-RAF: An Agentic, Retrieval-Augmented, Uncertainty-Gated Framework for Trustworthy Clinical Decision Support in Resource-Constrained Health Systems

2026-07-07

Abstract excerpt

<title>Abstract</title> <p>Large language models (LLMs) now approach or exceed expert-level performance on standardised medical examinations, and retrieval-augmented generation (RAG) substantially reduces their tendency to fabricate clinical facts. Independently, agentic architectures that interleave reasoning with tool use have begun to appear in medicine as multi-agent diagnostic assistants. Yet these three adv...

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Literature Corpus work: 5e37ee94-c479-544b-833d-98fc744a8af9
DOI: 10.21203/rs.3.rs-10259285/v1

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