Clinical Reasoning

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Clinical reasoning asks how systems can turn symptoms, records, test results, and images into diagnoses and care decisions while handling uncertainty and missing information. Current methods include retrieval from guidelines and knowledge graphs, Bayesian or symbolic reasoning, structured prompting and reinforcement learning, and agents that ask follow-up questions or coordinate specialist perspectives. Work increasingly evaluates multi-turn consultations, longitudinal EHR tasks, and multimodal cases, measuring evidence use, calibration, safety, and decision quality alongside diagnostic accuracy. A central tension is that strong exam or static-case performance does not reliably translate to consistent, evidence-grounded decisions in interactive clinical settings, making prospective validation and trustworthy process evaluation important open challenges.

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184 papers19 papers in the last four weeks, up 6% on the four weeks before. 0.1% of all new papers.

Improving Clinical Diagnosis with Counterfactual Multi-Agent Reasoning
Mar 29, 2026Zhiwen You, Xi Chen, Aniket Vashishtha +5Medical Diagnosis Clinical Decision Support
University of Illinois Urbana-Champaign, Urbana, IL, USA · Independent Researcher · Jacobi Medical Center, Albert Einstein College of Medicine, NY, USA +2
ClinicalAgents: Multi-Agent Orchestration for Clinical Decision Making with Dual-Memory
Mar 27, 2026Zhuohan Ge, Haoyang Li, Yubo Wang +3Clinical Decision-Making Multi-Agent LLM Systems
The Hong Kong Polytechnic University, Hong Kong SAR, China · The Hong Kong University of Science and Technology, Hong Kong SAR, China
Clinical Reasoning AI for Oncology Treatment Planning: A Multi-Specialty Case-Based Evaluation
Mar 27, 2026Philippe E. Spiess, Md Muntasir Zitu, Alison Walker +33Clinical Decision Support Oncology
Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL 33612, USA. · Innova Montréal Inc., IT Services and Consulting, Montréal, QC, Canada. · Oncobrain, Inc., Tampa, FL, USA. +1
Doctorina MedBench: A Dialogue-Based Benchmark and Evaluation Framework for Agent-Based Medical AI
Mar 26, 2026Anna Kozlova, Stanislau Salavei, Pavel Satalkin +3Medical AI Agents AI Agent Benchmarks
A.I. Doctor Medical Assist LTD, 13 Myrtiotissis Street, Aqua Mansions, Office 1, Germasogeia, 4041 Limassol, Cyprus
Multi-Agent Reasoning with Consistency Verification Improves Uncertainty Calibration in Medical MCQA
Mar 25, 2026John Ray B. MartinezUncertainty Calibration Medical QA
Department of Data Science and Analytics, Harrisburg University of Science and Technology
GSEM: Graph-based Self-Evolving Memory for Experience Augmented Clinical Reasoning
Mar 23, 2026Xiao Han, Yuzheng Fan, Sendong Zhao +2Memory-Augmented Language Model Agents Graph-Based Agent Memory
Research Center for Social Computing and Interactive Robotics, Harbin Institute of Technology, China
Mind the Rarities: Can Rare Skin Diseases Be Reliably Diagnosed via Diagnostic Reasoning?
Mar 19, 2026Yang Liu, Jiyao Yang, Hongjin Zhao +10Rare Disease Diagnosis Medical VLMs
Carnegie Mellon University · University of Alabama at Birmingham · Australian National University +3
Medical Reasoning with Large Language Models: A Survey and MR-Bench
Mar 17, 2026Xiaohan Ren, Chenxiao Fan, Wenyin Ma +4Medical Reasoning Clinical Reasoning
School of Cyber Science and Technology, University of Science and Technology of China, Anhui, China · School of Artificial Intelligence and Data Science, University of Science and Technology of China, Anhui, China · Department of Infectious Disease, The First Affiliated Hospital of USTC, Anhui, China +2
ECG-Reasoning-Benchmark: A Benchmark for Evaluating Clinical Reasoning Capabilities in ECG Interpretation
Mar 15, 2026Jungwoo Oh, Hyunseung Chung, Junhee Lee +6Electrocardiogram Interpretation Clinical Reasoning
KAIST · Ajou University School of Medicine · Yonsei University College of Medicine +1
Clinician input steers AI toward accurate and harmful recommendations
Mar 14, 2026Ivan Lopez, Selin S. Everett, Bryan J. Bunning +10Medical LLMs Clinical Language Model Evaluation
Department of Biomedical Data Science, Stanford University, Stanford, CA, USA · Stanford University School of Medicine, Stanford, CA, USA · Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA +14
Emulating Clinician Cognition via Self-Evolving Deep Clinical Research
Mar 11, 2026Ruiyang Ren, Yuhao Wang, Yunsen Liang +8Medical Diagnosis Clinical Decision Support
Gaoling School of Artificial Intelligence, Renmin University of China, Beijing, China. · Peking University Third Hospital, Beijing, China. · Baidu Inc., Beijing, China. +2
MedMASLab: A Unified Orchestration Framework for Benchmarking Multimodal Medical Multi-Agent Systems
Mar 10, 2026Yunhang Qian, Xiaobin Hu, Jiaquan Yu +6Multi-Agent Systems Multimodal Agents
National University of Singapore · University of Science and Technology of China · Fudan University +3
From Days to Minutes: An Autonomous AI Agent Achieves Reliable Clinical Triage in Remote Patient Monitoring
Mar 10, 2026Seunghwan Kim, Tiffany H. Kung, Heena Verma +8Remote Patient Monitoring Clinical Triage
AnsibleHealth Inc., San Francisco, USA · AnsibleHealth Inc., San Francisco, CA, USA · Stanford School of Medicine, Stanford, USA +3
A prospective clinical feasibility study of a conversational diagnostic AI in an ambulatory primary care clinic
Mar 9, 2026Peter Brodeur, Jacob M. Koshy, Anil Palepu +45Healthcare Medical LLMs
DERM-3R: A Resource-Efficient Multimodal Agents Framework for Dermatologic Diagnosis and Treatment in Real-World Clinical Settings
Mar 6, 2026Jirui Dai, Zhendong Wang, Chongjing Wang +7Traditional Chinese Medicine Dermatology
MedCoRAG: Interpretable Hepatology Diagnosis via Hybrid Evidence Retrieval and Multispecialty Consensus
Mar 5, 2026Zheng Li, Jiayi Xu, Zhikai Hu +4Medical Diagnosis Clinical Decision Support
School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China · School of Artificial Intelligence, Jilin University, Changchun, 130015, China · Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, 130033, China +2
Evaluating GPT-5 as a Multimodal Clinical Reasoner: A Landscape Commentary
Mar 5, 2026Alexandru Florea, Shansong Wang, Mingzhe Hu +5Clinical Reasoning Multimodal QA
Department of Radiation Oncology, Winship Cancer Institute, Emory University School of Medicine · Department of Biomedical Engineering, Georgia Institute of Technology
MIND: Unified Inquiry and Diagnosis RL with Criteria Grounded Clinical Supports for Psychiatric Consultation
Mar 4, 2026Guoyi Li, Shihao Xu, Jiatong Ma +4Healthcare Evidence-Grounded Reasoning
EverMind AI Inc., California, USA · Venus Team, Ant Group · Tianqiao and Chrissy Chen Institute, Shanghai, China +3
NeuroSymb-MRG: Differentiable Abductive Reasoning with Active Uncertainty Minimization for Radiology Report Generation
Mar 2, 2026Rong Fu, Yiqing Lyu, Chunlei Meng +9Radiology Report Generation Clinical Reasoning
University of Macau · Tsinghua University · Fudan University +6
TARSE: Test-Time Adaptation via Retrieval of Skills and Experience for Reasoning Agents
Mar 1, 2026Junda Wang, Zonghai Tao, Hansi Zeng +3Clinical QA LLM Agent Skill Retrieval
University of Massachusetts Amherst, MA, USA · University of Massachusetts Lowell, MA, USA
MedCollab: IBIS-Guided Multi-Agent Collaboration with Hierarchical Disease Relation Chains for Clinical Diagnosis
Mar 1, 2026Yuqi Zhan, Xinyue Wu, Tianyu Lin +6Multi-Agent LLM Systems Medical Report Generation
Hangzhou Dianzi University · Zhejiang University · Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children and Adolescents’ Health and Diseases
MedGPT-oss: Training a General-Purpose Vision-Language Model for Biomedicine
Mar 1, 2026Kai Zhang, Zhengqing Yuan, Cheng Peng +10Healthcare Multimodal Pretraining
Department of Computer Science and Engineering, Lehigh University · Department of Computer Science and Engineering, University of Notre Dame · Department of Health Outcomes & Biomedical Informatics, University of Florida +3
How Well Do Multimodal Models Reason on ECG Signals?
Feb 27, 2026Maxwell A. Xu, Harish Haresamudram, Catherine W. Liu +11Electrocardiogram Interpretation Multimodal Model Evaluation
University of Illinois Urbana Champaign · Google Inc · Rush University +4
CXReasonAgent: Evidence-Grounded Diagnostic Reasoning Agent for Chest X-rays
Feb 26, 2026Hyungyung Lee, Hangyul Yoon, Edward ChoiRadiology VLMs Clinical Reasoning
KAIST
TCM-DiffRAG: Personalized Syndrome Differentiation Reasoning Method for Traditional Chinese Medicine based on Knowledge Graph and Chain of Thought
Feb 26, 2026Jianmin Li, Ying Chang, Su-Kit Tang +4Traditional Chinese Medicine Graph Retrieval-Augmented Generation
1.Faculty of Applied Sciences, Macao Polytechnic University, R. de Luís Gonzaga Gomes, 999078, Macao, China. · 3.School of Basic Medical Sciences, Zhejiang Chinese Medical University, 548 Binwen Road, Binjiang District, Hangzhou 310053, China. · 6.Zhejiang Chinese Medical University – GANCAO DOCTOR Institute of Artificial Intelligence for Chinese Medicine +3
MedClarify: An information-seeking AI agent for medical diagnosis with case-specific follow-up questions
Feb 19, 2026Hui Min Wong, Philip Heesen, Pascal Janetzky +2Information Gain Medical LLMs
LMU Munich, Munich, Germany · Munich Center for Machine Learning, Germany · Department of Neuroradiology, Heidelberg University, Heidelberg, Germany
LiveClin: A Live Clinical Benchmark without Leakage
Feb 18, 2026Xidong Wang, Shuqi Guo, Yue Shen +6Clinical Language Model Evaluation Medical LLMs
The Chinese University of Hong Kong, ShenZhen · Ant Healthcare, Ant Group · The Ohio State University +1
Evidence-Grounded Subspecialty Reasoning: Evaluating a Curated Clinical Intelligence Layer on the 2025 Endocrinology Board-Style Examination
Feb 17, 2026Amir Hosseinian, MohammadReza Zare Shahneh, Umer Mansoor +3Clinical Language Model Evaluation Evidence-Grounded Reasoning
January AI · Stanford University
Think Like a Doctor: Conversational Diagnosis through the Exploration of Diagnostic Knowledge Graphs
Feb 2, 2026Jeongmoon Won, Seungwon Kook, Yohan JoHealthcare Medical Diagnosis
Graduate School of Data Science, Seoul National University
Towards Reliable Medical LLMs: Benchmarking and Enhancing Confidence Estimation of Large Language Models in Medical Consultation
Jan 22, 2026Zhiyao Ren, Yibing Zhan, Siyuan Liang +3Healthcare Clinical Reasoning
Nanyang Technological University, Singapore, Singapore. · Wuhan University, Wuhan, China.

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Improving Clinical Diagnosis with Counterfactual Multi-Agent Reasoning

Zhiwen You, Xi Chen, Aniket Vashishtha, Simo Du+4

University of Illinois Urbana-Champaign, Urbana, IL, USA · Independent Researcher · Jacobi Medical Center, Albert Einstein College of Medicine, NY, USA+2

Medical Diagnosis Clinical Decision Support Clinical Reasoning Counterfactual Reasoning in Language Models Multi-Agent Reasoning

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Clinical diagnosis is a complex reasoning process in which clinicians gather evidence, form hypotheses, and test them against alternative explanations. In medical training, this reasoning is explicitly developed through counterfactual questioning--e.g., asking how a diagnosis would change if a key symptom were absent or altered--to strengthen differential diagnosis skills. As large language model (LLM)-based systems are increasingly used for diagnostic support, ensuring the interpretability of their recommendations becomes critical. However, most existing LLM-based diagnostic agents reason over fixed clinical evidence without explicitly testing how individual findings support or weaken competing diagnoses. In this work, we propose a counterfactual multi-agent diagnostic framework inspired by clinician training that makes hypothesis testing explicit and evidence-grounded. Our framework introduces counterfactual case editing to modify clinical findings and evaluate how these changes affect competing diagnoses. We further define the Counterfactual Probability Gap, a method that quantifies how strongly individual findings support a diagnosis by measuring confidence shifts under these edits. These counterfactual signals guide multi-round specialist discussions, enabling agents to challenge unsupported hypotheses, refine differential diagnoses, and produce more interpretable reasoning trajectories. Across three diagnostic benchmarks and seven LLMs, our method consistently improves diagnostic accuracy over prompting and prior multi-agent baselines, with the largest gains observed in complex and ambiguous cases. Human evaluation further indicates that our framework produces more clinically useful, reliable, and coherent reasoning. These results suggest that incorporating counterfactual evidence verification is an important step toward building reliable AI systems for clinical decision support.