Differential Diagnosis

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Differential diagnosis studies how clinicians distinguish among conditions that can explain a patient’s symptoms, and how decision-support systems can help do this safely. Current methods include language models that retrieve clinical knowledge, track evidence and uncertainty, ask targeted questions, or coordinate specialist agents; conventional classifiers also use signals such as gait measurements. Evaluation spans medical case questions, EHRs, images, and interactive dialogue benchmarks, with growing attention to evidence use, dangerous alternatives, and diagnostic workup quality rather than just the final answer. Despite gains on curated cases, models remain unreliable in real-world settings and struggle with multimorbidity, missing or misleading evidence, and demographic bias.

Latest papers

27 papers1 paper in the last four weeks, down 67% on the four weeks before. 0.0% of all new papers.

Ontology-guided multi-agent reasoning for explainable differential diagnosis
Oct 26, 2026Roxana Ramona Szomiu, George Ursu, Adrian GrozaDifferential Diagnosis Clinical Reasoning
CLIMB: A Clinical Multimorbidity Benchmark for Diagnosing Co-occurring Conditions through Multiturn Conversations
Sep 28, 2026Yusuf Kesmen, Aniruddha Mukherjee, Yena Chang +7Medical Diagnosis Multi-Turn Dialogue Evaluation
EPFL · Aarhus University
Hyperbolic Graph Representation Learning for Differential Diagnosis on Biomedical Knowledge Graphs
Sep 16, 2026Pietro Miotto, Lucia Mellini, Tommaso Marzi +5KG Embedding Knowledge Graphs
Department of Computer Science, Università degli Studi di Milano, Milan, Italy · Università della Svizzera italiana (USI), Lugano, Switzerland · Politecnico di Milano, Milan, Italy +2
A Structured Debate-Mixture-of-Agents Framework for Complex Clinical Diagnostic Decision Support
Sep 4, 2026Chang Xia, Leilei Ouyang, Huimin Wang +2Multi-Agent LLM Systems Clinical Decision Support
College of Computer Science, Sichuan University, Chengdu 610207, China · West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China · Med-X Center for Informatics, Sichuan University, Chengdu 610041, China
NSIDDx: A Design Framework for Neuro-Symbolic, Practitioner-First Differential Diagnosis in Low-Resource Settings
Aug 31, 2026Aarav SinghRare Disease Diagnosis Healthcare
IIIT Naya Raipur
MTDiag: A Multi-Turn Diagnostic Dataset Towards Clinically Meaningful LLM Evaluation
Aug 25, 2026Pia Chouayfati, Alexander M. Fichtl, Miriam Anschütz +2Clinical Language Model Evaluation Differential Diagnosis
Technical University of Munich · Department of Internal Medicine, UT Southwestern
Social Chain of Thought: A Multi-Agent Architecture Grounded in Medical Differential Diagnosis Methodology
Aug 11, 2026Del Coburn, Scott Sanner, Dan SilverMulti-Agent Collaboration Clinical Reasoning
Department of Sociology University of Toronto · Department of Mechanical & Industrial Engineering University of Toronto
Auditing Evidence Use in Medical LLM Diagnosis
Jul 23, 2026Junchi Liao, Jiawen Deng, Fuji RenLLM Auditing Medical Diagnosis
University of Electronic Science and Technology of China Chengdu, China
Aletheia: An Offline-First Clinical Decision Support System for Differential Diagnosis in Low-Resource Healthcare Settings
Jul 14, 2026Joseph Walusimbi, Ann Move Oguti, Abubakhari Sserwadda +2Clinical Decision Support Healthcare
Department of Electronics and Computer Engineering, Soroti University, Soroti, Uganda · School of Health Sciences, Soroti University, Soroti, Uganda
A safety-oriented hypothetico-deductive framework for AI-assisted differential diagnosis
Jul 9, 2026Fan Ma, Mauro Giuffrè, Donald Wright +12Scientific Reasoning Medical Diagnosis
Department of Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, USA · Department of Medical, Surgical and Health Sciences, Università degli Studi di Trieste, Trieste, Italy · Department of Emergency Medicine, Yale School of Medicine, Yale University, New Haven, USA +3
Ekka: Automated Diagnosis of Silent Errors in LLM Inference
Jun 3, 2026Yile Gu, Zhen Zhang, Shaowei Zhu +4Software Engineering LLM Serving
University of Washington · 2Amazon Web Services.
Gender-Dependent Diagnostic Substitution in LLM Medical Triage: Same Symptoms, Unequal Urgency
Jun 2, 2026Qi Han WongGender Bias in Language Models Clinical Triage
DDX-TRACE: A Benchmark for Medical Diagnostic Trajectories in VLMs
May 22, 2026Jiazhen Pan, Weixiang Shen, Jun Li +7Medical Imaging Radiology VLMs
Technical University of Munich (TUM) · TUM University Hospital · Munich Center for Machine Learning (MCML) +3
MedExpMem: Adapting Experience Memory for Differential Diagnosis
May 20, 2026Qianhan Feng, Zhongzhen Huang, Yakun Zhu +4Radiology VLMs Healthcare
The Chinese University of Hong Kong · Shanghai Jiao Tong University · Shanghai Innovation Institue
Medical Model Synthesis Architectures: A Case Study
May 10, 2026Katherine M. Collins, Marlene Berke, Ilia Sucholutsky +6Explainable Artificial Intelligence Healthcare
MIT · University of Cambridge · Princeton University +8
MedAction: Towards Active Multi-turn Clinical Diagnostic LLMs
May 8, 2026Hsin-Ling Hsu, Zizheng Wang, Donghua Zhang +9Healthcare Medical Diagnosis
National Chengchi University · Georgetown University · University of Michigan +3
SymptomAI: Toward a Conversational AI Agent for Everyday Symptom Assessment
May 5, 2026Joseph Breda, Fadi Yousif, Beszel Hawkins +30Healthcare Medical Diagnosis
Google Research · Work done while at Google Research · Google DeepMind
Are Multimodal LLMs Ready for Clinical Dermatology? A Real-World Evaluation in Dermatology
May 1, 2026Roy Jiang, Hyunjae Kim, Zhenyue Qin +8Differential Diagnosis Clinical Triage
Department of Dermatology, Yale School of Medicine, Yale University, New Haven, CT, USA · Department of Bioinformatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA · Yale School of Medicine, Yale University, New Haven, CT, USA
MultiDx: A Multi-Source Knowledge Integration Framework towards Diagnostic Reasoning
Apr 27, 2026Yimin Deng, Zhenxi Lin, Yejing Wang +9Knowledge Augmentation for Language Models Medical Diagnosis
Xi’an Jiaotong University · City University of Hong Kong · Tencent Jarvis Lab +1
SymptomWise: A Deterministic Reasoning Layer for Reliable and Efficient AI Systems
Apr 7, 2026Isaac Henry, Avery Byrne, Christopher Giza +2Clinical Decision Support Clinical Reasoning
University of California Los Angeles, David Geffen School of Medicine · University of Southern California
HeartAgent: An Autonomous Agent System for Explainable Differential Diagnosis in Cardiology
Mar 11, 2026Shuang Zhou, Kai Yu, Song Wang +11Clinical Decision Support Differential Diagnosis
Division of Computational Health Sciences, Department of Surgery, University of Minnesota, Minneapolis, MN, USA · Department of Computer Science, University of Central Florida, Orlando, FL, USA · College of Science and Engineering, University of Minnesota, Minneapolis, MN, USA +6
Topological descriptors of foot clearance gait dynamics improve differential diagnosis of Parkinsonism
Mar 6, 2026Jhonathan Barrios, Wolfram Erlhagen, Miguel F. Gago +2Parkinson's Disease Classification Differential Diagnosis
Centre of Mathematics (CMAT), School of Sciences, University of Minho, Portugal · Neurology Departmet, Hospital da Senhora da Oliveira, Portugal · ICVS, School of Medicine, University of Minho, Portugal +3
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
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
Can Agents Distinguish Visually Hard-to-Separate Diseases in a Zero-Shot Setting? A Pilot Study
Feb 26, 2026Zihao Zhao, Frederik Hauke, Juliana De Castilhos +2Medical Image Classification Multimodal Agents
Department of Diagnostic and Interventional Radiology, University Hospital Aachen, 52074 Aachen, Germany
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
Few shot chain-of-thought driven reasoning to prompt LLMs for open ended medical question answering
Mar 7, 2024Saeel Sandeep Nachane, Ojas Gramopadhye, Prateek Chanda +5Healthcare Medical Diagnosis
2Indian Institute of Technology Bombay · 1IBM Research

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Ontology-guided multi-agent reasoning for explainable differential diagnosis

Roxana Ramona Szomiu, George Ursu, Adrian Groza

Differential Diagnosis Clinical Reasoning Explainable Artificial Intelligence Medical LLMs Multi-Agent LLM Systems

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Effective differential diagnosis depends on well structured and unambiguous patient case descriptions, since incomplete or ambiguous clinical information readily leads to diagnostic errors and inconsistent reasoning. Large Language Models (LLMs) have recently shown promising capabilities in medical question answering and clinical reasoning; however, even when achieving competitive performance on medical benchmarks, they often rely on pattern recognition learned from training data rather than grounded clinical evidence, and can generate plausible yet unsupported diagnostic conclusions. Their reasoning remains largely opaque, making it difficult for clinicians to assess the evidence and rationale behind a given recommendation. To address this gap, we propose an ontology-guided, multiagent differential diagnosis framework that replicates the iterative reasoning process of physicians. The framework grounds diagnostic inference in a structured, expert-curated medical knowledge base, enabling interpretation of symptoms, clinical findings, or disease relationships, while decomposing diagnosis into explicit, auditable reasoning steps. This ontology-based grounding constrains inference to evidence-backed associations, reducing hallucination and improving diagnostic transparency, traceability, and consistency. The system then identifies the most discriminative missing symptoms and generates targeted follow-up questions to reduce uncertainty through a process that mirrors to clinical inquiry. Together, these components improve the reliability, explainability, and diagnostic accuracy of AI-assisted differential diagnosis. The source code is publicly available.