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From Evidence-Based Medicine to Knowledge Graph: Retrieval-Augmented Generation for Sports Rehabilitation and a Domain Benchmark

A paper proposing a framework for integrating evidence-based medicine principles into knowledge graph construction and retrieval.

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From Evidence-Based Medicine to Knowledge Graph: Retrieval-Augmented Generation for Sports Rehabilitation and a Domain Benchmark

By Jinning Zhang, Jie Song, Wenhui Tu, Zecheng Li, Jingxuan Li, Jin Li, Xuan Liu, Taole ShaarXiv (Cornell University)
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The authors present SR-RAG, an EBM-adapted GraphRAG framework that integrates the PICO framework into knowledge graph construction and retrieval. They also propose Bayesian Evidence Tier Reranking (BETR) to calibrate ranking scores by evidence grade without predefined weights.

The paper is validated in sports rehabilitation with a released knowledge graph and benchmark.

Abstract

The authors present SR-RAG, an EBM-adapted GraphRAG framework that integrates the PICO framework into knowledge graph construction and retrieval. They also propose Bayesian Evidence Tier Reranking (BETR) to calibrate ranking scores by evidence grade without predefined weights. The paper is validated in sports rehabilitation with a released knowledge graph and benchmark.

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evidence-based medicineknowledge graph constructionrerankingsports rehabilitationKnowledge GraphsRetrieval & RAGLarge Language ModelsSemantic Interoperability
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