mlsanityData to 14 Oct 2026

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

arXiv 2601.00216 ↗First posted 1 Jan 2026cs.CLcited by 0

On the map: Retrieval-augmented generation → Medical and biomedical RAG

Abstract (arXiv)

Current medical retrieval-augmented generation (RAG) approaches overlook evidence-based medicine (EBM) principles, leading to two key gaps: (1) the lack of PICO alignment between queries and retrieved evidence, and (2) the absence of evidence hierarchy considerations during reranking. We present SR-RAG, an EBM-adapted GraphRAG framework that integrates the PICO framework into knowledge graph construction and retrieval, and proposes Bayesian Evidence Tier Reranking (BETR) to calibrate ranking scores by evidence grade without predefined weights. Validated in sports rehabilitation, we release a knowledge graph (357,844 nodes, 371,226 edges) and a benchmark of 1,637 QA pairs. SR-RAG achieves 0.812 evidence recall@10, 0.830 nugget coverage, 0.819 answer faithfulness, 0.882 semantic similarity, and 0.788 PICOT match accuracy, substantially outperforming five baselines. Five expert clinicians rated the system 4.66--4.84 on a 5-point Likert scale, and system rankings are preserved on a human-verified gold subset (n=80).

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 34 of its 65 references that are in the map. First posted on arXiv 1 Jan 2026.

Builds on

34 of 65 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025META-RAG: Meta-Analysis-Inspired Evidence-Re-Ranking Method for Retrieval-Augmented Generation in Evidence-Based Medicine28 Oct
  2. 2025PICOs-RAG: PICO-supported Query Rewriting for Retrieval-Augmented Generation in Evidence-Based Medicine28 Oct
  3. 2025ModernBERT + ColBERT: Enhancing biomedical RAG through an advanced re-ranking retriever6 Oct
  4. 2024Rationale-Guided Retrieval Augmented Generation for Medical Question Answering1 Nov
  5. 2024Benchmarking Retrieval-Augmented Generation for Medicine20 Feb
  6. 2023MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering27 Sep

Other references · 28

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  3. 2024GPT-4o System Cardcited by 4,588
  4. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,839
  5. 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,453
  6. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,282
  7. 2020ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERTcited by 1,178
  8. 2024M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillationcited by 1,073
  9. 2022Precise Zero-Shot Dense Retrieval without Relevance Labelscited by 517
  10. 2024LightRAG: Simple and Fast Retrieval-Augmented Generationcited by 315
  11. 2023ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systemscited by 265
  12. 2020Sparse, Dense, and Attentional Representations for Text Retrievalcited by 214
16 more
  1. 2024Corrective Retrieval Augmented Generationcited by 197
  2. 2023Query2doc: Query Expansion with Large Language Modelscited by 149
  3. 2024Reducing hallucination in structured outputs via Retrieval-Augmented Generationcited by 93
  4. 2024A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directionscited by 70
  5. 2025Baichuan-M2: Scaling Medical Capability with Large Verifier Systemcited by 59
  6. 2024LumberChunker: Long-Form Narrative Document Segmentationcited by 36
  7. 2024Docling Technical Reportcited by 34
  8. 2024Initial Nugget Evaluation Results for the TREC 2024 RAG Track with the AutoNuggetizer Frameworkcited by 28
  9. 2025Youtu-GraphRAG: Vertically Unified Agents for Graph Retrieval-Augmented Complex Reasoningcited by 22
  10. 2024Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perceptioncited by 17
  11. 2024Language and Multimodal Models in Sports: A Survey of Datasets and Applicationscited by 10
  12. 2025Fantastic (small) Retrievers and How to Train Them: mxbai-edge-colbert-v0 Tech Reportcited by 10
  13. 2024HyQE: Ranking Contexts with Hypothetical Query Embeddingscited by 6
  14. 2024MEG: Medical Knowledge-Augmented Large Language Models for Question Answeringcited by 6
  15. 2025Med-R2: Crafting Trustworthy LLM Physicians via Retrieval and Reasoning of Evidence-Based Medicinecited by 5
  16. 2025Refine Medical Diagnosis Using Generation Augmented Retrieval and Clinical Practice Guidelinescited by 1

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  2. 2025Rethinking Retrieval-Augmented Generation for Medicine: A Large-Scale, Systematic Expert Evaluation and Practical Insights
  3. 2025R2MED: A Benchmark for Reasoning-Driven Medical Retrieval
  4. 2024Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation
  5. 2026Building evidence-based knowledge bases from full-text literature for disease-specific biomedical reasoning
  6. 2024Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
  7. 2026A Hybrid Retrieval and Reranking Framework for Evidence-Grounded Retrieval-Augmented Generation
  8. 2025Query-driven Document-level Scientific Evidence Extraction from Biomedical Studies