mlsanityData to 7 Oct 2026

MedCoT-RAG: Causal Chain-of-Thought RAG for Medical Question Answering

arXiv 2508.15849 ↗First posted 20 Aug 2025cs.CL cs.IRcited by 5

On the map: LLM reasoning → Clinical and biomedical applications

Abstract (arXiv)

Large language models (LLMs) have shown promise in medical question answering but often struggle with hallucinations and shallow reasoning, particularly in tasks requiring nuanced clinical understanding. Retrieval-augmented generation (RAG) offers a practical and privacy-preserving way to enhance LLMs with external medical knowledge. However, most existing approaches rely on surface-level semantic retrieval and lack the structured reasoning needed for clinical decision support. We introduce MedCoT-RAG, a domain-specific framework that combines causal-aware document retrieval with structured chain-of-thought prompting tailored to medical workflows. This design enables models to retrieve evidence aligned with diagnostic logic and generate step-by-step causal reasoning reflective of real-world clinical practice. Experiments on three diverse medical QA benchmarks show that MedCoT-RAG outperforms strong baselines by up to 10.3% over vanilla RAG and 6.4% over advanced domain-adapted methods, improving accuracy, interpretability, and consistency in complex medical tasks.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 16 of its 19 references that are in the map. First posted on arXiv 20 Aug 2025.

Builds on

16 of 19 references.

References · 16

  1. 2024The Llama 3 Herd of Modelscited by 14,192
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  4. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,324
  5. 2024Benchmarking Retrieval-Augmented Generation for Medicinecited by 326
  6. 2022LinkBERT: Pretraining Language Models with Document Linkscited by 209
  7. 2023MedCPT: Contrastive Pre-trained Transformers with Large-scale PubMed Search Logs for Zero-shot Biomedical Information Retrievalcited by 182
  8. 2023Med-HALT: Medical Domain Hallucination Test for Large Language Modelscited by 156
  9. 2024Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generationcited by 89
  10. 2025MedRAG: Enhancing Retrieval-augmented Generation with Knowledge Graph-Elicited Reasoning for Healthcare Copilotcited by 83
  11. 2024Rationale-Guided Retrieval Augmented Generation for Medical Question Answeringcited by 41
  12. 2024Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHRscited by 39
4 more
  1. 2024HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversationscited by 31
  2. 2025CDF-RAG: Causal Dynamic Feedback for Adaptive Retrieval-Augmented Generationcited by 6
  3. 2025RGAR: Recurrence Generation-augmented Retrieval for Factual-aware Medical Question Answeringcited by 5
  4. 2025K-COMP: Retrieval-Augmented Medical Domain Question Answering With Knowledge-Injected Compressorcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 4.

5 papers.

  1. 2026CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretationcited by 2
  2. 2025Contradictions in Context: Challenges for Retrieval-Augmented Generation in Healthcarecited by 1
  3. 2026Foundation Models for Medical Imaging: Status, Challenges, and Directionscited by 0
  4. 2026To Reason or Not to: Selective Chain-of-Thought in Medical Question Answeringcited by 0
  5. 2026PerCaM-Health: Personalized Dynamic Causal Graphs for Healthcare Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Comprehensive and Practical Evaluation of Retrieval-Augmented Generation Systems for Medical Question Answering
  2. 2025Optimizing Medical Question-Answering Systems: A Comparative Study of Fine-Tuned and Zero-Shot Large Language Models with RAG Framework
  3. 2026A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering
  4. 2023MKRAG: Medical Knowledge Retrieval Augmented Generation for Medical Question Answering
  5. 2025Talk Before You Retrieve: Agent-Led Discussions for Better RAG in Medical QA
  6. 2026Hybrid-IR: Dual-Path Hybrid Retrieval with Iterative Reasoning for Complex Medical Question Answering
  7. 2025RAR2: Retrieval-Augmented Medical Reasoning via Thought-Driven Retrieval
  8. 2025MedTrust-RAG: Evidence Verification and Trust Alignment for Biomedical Question Answering