mlsanityData to 14 Oct 2026

DoctorRAG: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients

arXiv 2505.19538 ↗First posted 26 May 2025cs.CL cs.AI cs.CEcited by 5

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

Abstract (arXiv)

Existing medical RAG systems mainly leverage knowledge from medical knowledge bases, neglecting the crucial role of experiential knowledge derived from similar patient cases -- a key component of human clinical reasoning. To bridge this gap, we propose DoctorRAG, a RAG framework that emulates doctor-like reasoning by integrating both explicit clinical knowledge and implicit case-based experience. DoctorRAG enhances retrieval precision by first allocating conceptual tags for queries and knowledge sources, together with a hybrid retrieval mechanism from both relevant knowledge and patient. In addition, a Med-TextGrad module using multi-agent textual gradients is integrated to ensure that the final output adheres to the retrieved knowledge and patient query. Comprehensive experiments on multilingual, multitask datasets demonstrate that DoctorRAG significantly outperforms strong baseline RAG models and gains improvements from iterative refinements. Our approach generates more accurate, relevant, and comprehensive responses, taking a step towards more doctor-like medical reasoning systems.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 29 of its 44 references that are in the map. First posted on arXiv 26 May 2025.

Builds on

29 of 44 references.

Closest ancestors · 9

Same direction, newest first

  1. 2025The Multi-Round Diagnostic RAG Framework for Emulating Clinical Reasoning10 Apr
  2. 2025MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilot6 Feb
  3. 2024TC-RAG:Turing-Complete RAG's Case study on Medical LLM Systems17 Aug
  4. 2024Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation8 Aug
  5. 2024BioRAG: A RAG-LLM Framework for Biological Question Reasoning2 Aug
  6. 2024Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions1 Aug
  7. 2024Two-Layer Retrieval-Augmented Generation Framework for Low-Resource Medical Question Answering Using Reddit Data: Proof-of-Concept Study29 May
  8. 2024Benchmarking Retrieval-Augmented Generation for Medicine20 Feb
  9. 2023Almanac: Retrieval-Augmented Language Models for Clinical Medicine1 Mar

Other references · 20

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  3. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  4. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 8,065
  5. 2019BERTScore: Evaluating Text Generation with BERTcited by 5,512
  6. 2023Qwen Technical Reportcited by 3,344
  7. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,898
  8. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,212
  9. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,356
  10. 2024ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Toolscited by 1,121
  11. 2023SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Modelscited by 810
  12. 2023RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedbackcited by 625
8 more
  1. 2022DDXPlus: A New Dataset For Automatic Medical Diagnosiscited by 88
  2. 2024RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processingcited by 25
  3. 2024REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language Modelscited by 23
  4. 2025Can Textual Gradient Work in Federated Learning?cited by 15
  5. 2022DialMed: A Dataset for Dialogue-based Medication Recommendationcited by 12
  6. 2025AutoMedPrompt: A New Framework for Optimizing LLM Medical Prompts Using Textual Gradientscited by 7
  7. 2025Biomedical Knowledge Graph: A Survey of Domains, Tasks, and Real-World Applicationscited by 6
  8. 2024Knowledge Editing on Black-box Large Language Modelscited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025MedReflect: Teaching Medical LLMs to Self-Improve via Reflective Correctioncited by 8
  2. 2025One Patient, Many Contexts: Scaling Medical AI with Contextual Intelligencecited by 2
  3. 2026Med-CoReasoner: Reducing Language Disparities in Medical Reasoning via Language-Informed Co-Reasoningcited by 2
  4. 2026StepGap: A Hybrid NLI-LLM Checker for Step-Level Evidence-Gap Detectionin Multi-Hop Question Answeringcited by 0
  5. 2026Taking the PULSE of Medical Reasoning: Step-Level Retrieval Timing for Knowledge-Grounded Inferencecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025MedCoT-RAG: Causal Chain-of-Thought RAG for Medical Question Answering
  2. 2026SEMA-RAG: A Self-Evolving Multi-Agent Retrieval-Augmented Generation Framework for Medical Reasoning
  3. 2026CBR-to-SQL: Rethinking Retrieval-based Text-to-SQL using Case-based Reasoning in the Healthcare Domain
  4. 2025Talk Before You Retrieve: Agent-Led Discussions for Better RAG in Medical QA
  5. 2025R2MED: A Benchmark for Reasoning-Driven Medical Retrieval
  6. 2025Agentic Medical Knowledge Graphs Enhance Medical Question Answering: Bridging the Gap Between LLMs and Evolving Medical Knowledge
  7. 2025RAR2: Retrieval-Augmented Medical Reasoning via Thought-Driven Retrieval
  8. 2025POLYRAG: Integrating Polyviews into Retrieval-Augmented Generation for Medical Applications