mlsanityData to 14 Oct 2026

Medical Reasoning in LLMs: An In-Depth Analysis of DeepSeek R1

arXiv 2504.00016 ↗First posted 27 Mar 2025cs.CLcited by 5

On the map: LLM reasoning → Clinical and biomedical applications

Abstract (arXiv)

Integrating large language models (LLMs) like DeepSeek R1 into healthcare requires rigorous evaluation of their reasoning alignment with clinical expertise. This study assesses DeepSeek R1's medical reasoning against expert patterns using 100 MedQA clinical cases. The model achieved 93% diagnostic accuracy, demonstrating systematic clinical judgment through differential diagnosis, guideline-based treatment selection, and integration of patient-specific factors. However, error analysis of seven incorrect cases revealed persistent limitations: anchoring bias, challenges reconciling conflicting data, insufficient exploration of alternatives, overthinking, knowledge gaps, and premature prioritization of definitive treatment over intermediate care. Crucially, reasoning length correlated with accuracy - shorter responses (<5,000 characters) were more reliable, suggesting extended explanations may signal uncertainty or rationalization of errors. While DeepSeek R1 exhibits foundational clinical reasoning capabilities, recurring flaws highlight critical areas for refinement, including bias mitigation, knowledge updates, and structured reasoning frameworks. These findings underscore LLMs' potential to augment medical decision-making through artificial reasoning but emphasize the need for domain-specific validation, interpretability safeguards, and confidence metrics (e.g., response length thresholds) to ensure reliability in real-world applications.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Clinical and biomedical applications, one of 17 directions in LLM reasoning. Builds on 12 of its 55 references that are in the map. First posted on arXiv 27 Mar 2025.

Builds on

12 of 55 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025Med-R1: Reinforcement Learning for Generalizable Medical Reasoning in Vision-Language Models18 Mar
  2. 2024MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical Reasoning3 Jun
  3. 2024JMLR: Joint Medical LLM and Retrieval Training for Enhancing Reasoning and Professional Question Answering Capability27 Feb

Other references · 9

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  3. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  4. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  5. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,356
  6. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 638
  7. 2024The Platonic Representation Hypothesiscited by 382
  8. 2024Your Mixture-of-Experts LLM Is Secretly an Embedding Model For Freecited by 37
  9. 2023Augmenting Black-box LLMs with Medical Textbooks for Biomedical Question Answeringcited by 11

Built on by

Cited by year (2026 to 14 Oct)

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

5 papers.

  1. 2025Evaluating Reasoning Faithfulness in Medical Vision-Language Models using Multimodal Perturbationscited by 9
  2. 2025Foundation Models in Biomedical Imaging: Turning Hype into Realitycited by 2
  3. 2025Cognitive bias in LLM reasoning compromises interpretation of clinical oncology notescited by 0
  4. 2025Toward an AI Reasoning-Enabled System for Patient-Clinical Trial Matchingcited by 0
  5. 2026Rethinking LLM Verification: Evidence Structure, Uncertainty, and Selective Refinementcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Quantifying the Reasoning Abilities of LLMs on Real-world Clinical Cases
  2. 2025Reasoning LLMs in the Medical Domain: A Literature Survey
  3. 2026Aligning Clinical Needs and AI Capabilities: A Survey on LLMs for Medical Reasoning
  4. 2025MedCaseReasoning: Evaluating and learning diagnostic reasoning from clinical case reports
  5. 2025Automating Expert-Level Medical Reasoning Evaluation of Large Language Models
  6. 2026Medical Reasoning with Large Language Models: A Survey and MR-Bench
  7. 2026CLExEval: A Human-in-the-Loop Framework for Qualitative Evaluation of LLM Clinical Reasoning
  8. 2025Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications