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Graph-Augmented Retrieval for Digital Evidence-Based Medical Synthesis: A Proof-of-Concept Study on Topology-Aware Mechanistic Narrative Generation

2026-02-19

Abstract excerpt

<h4>Background</h4> Retrieval-augmented generation (RAG) frameworks such as RAPID [1] have demonstrated that staged planning and retrieval grounding improve long-form text generation. However, most implementations remain similarity-driven and open-domain, lacking the epistemic safeguards required for biomedical synthesis, where mechanistic completeness, temporal governance, traceability, and explicit gap classifi...

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Literature Corpus work
01f4d84a-b79f-56cb-8e64-fff4185874b9
DOI
10.64898/2026.02.18.26346545
Open publication

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Graph-Augmented Retrieval for Digital Evidence-Based Medical Synthesis: A Proof-of-Concept Study on Topology-Aware Mechanistic Narrative GenerationDOI 10.64898/2026.02.18.26346545
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