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C-RLM: Schema-Enforced Recursive Synthesis for Auditable, Long-Context Clinical Documentation

2026-01-26 health informatics Title + abstract only
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Clinical decision-making for multi-morbid patients requires synthesizing evidence from lengthy, fragmented records--a task that exposes the limitations of standard Retrieval-Augmented Generation (RAG) and long-context Large Language Models (LLMs), which often lose critical information or lack auditability. We introduce the Clinical-Recursive Language Model (C-RLM), a framework that reframes evidence synthesis as a structured, recursive compilation process rather than a single-pass retrieval task...

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