Medical LLMs

LLM: Large Language Model

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26 papers in the last four weeks, up 160% on the four weeks before. 0.3% of all new papers.

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Latest papers 238

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Synthesis and Evaluation of Long-term History-aware Medical Dialogue
May 19, 2026Hebin Hu, Renke Dai, Ah-Hwee Tan +1Healthcare AI Agent Benchmarks
South-Central Minzu University Wuhan, China · Singapore Management University Singapore, Singapore
Prompting language influences diagnostic reasoning and accuracy of large language models
May 18, 2026Adrien Bazoge, Josselin Corvellec, Sofiane Djillali Sid-Ahmed +1Multilingual Language Model Evaluation LLM Prompting
Data Clinic, Nantes University Hospital, France
Evaluating the Utility of Personal Health Records in Personalized Health AI
May 18, 2026Rory Sayres, Kejia Chen, Ayush Jain +19LLM Personalization Healthcare
1Google Research · †Work done while at Google Research
BELIEF: Structured Evidence Modeling and Uncertainty-Aware Fusion for Biomedical Question Answering
May 17, 2026Chang Zong, Hao Ning, Siliang Tang +2Healthcare Evidence-Grounded Reasoning
Fully Open Meditron: An Auditable Pipeline for Clinical LLMs
May 15, 2026Xavier Theimer-Lienhard, Mushtaha El-Amin, Fay Elhassan +5Healthcare LLM Auditing
LiGHT, EPFL
Few-Shot Large Language Models for Actionable Triage Categorization of Online Patient Inquiries
May 15, 2026Liqi Zhou, Jiafu LiHealthcare Clinical Triage
COTCAgent: Preventive Consultation via Probabilistic Chain-of-Thought Completion
May 14, 2026Zihan Deng, Xiaozhen Zhong, Chuanzhi XuHealthcare Clinical Decision Support
School of Computing and Data Science, The University of Hong Kong · 2Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China · School of Computer Science, The University of Sydney
Quantifying and Mitigating Premature Closure in Frontier LLMs
May 14, 2026Rebecca Handler, Suhana Bedi, Nigam ShahHealthcare LLM Prompting
Department of Medicine, Stanford University · Department of Biomedical Data Science, Stanford University
Agentifying Patient Dynamics within LLMs through Interacting with Clinical World Model
May 14, 2026Minghao Wu, Yuting Yan, Zhenyang Cai +9Agentic RL Clinical Decision Support
The Chinese University of Hong Kong, Shenzhen · Beijing Hospital
IndicMedDialog: A Parallel Multi-Turn Medical Dialogue Dataset for Accessible Healthcare in Indic Languages
May 13, 2026Shubham Kumar Nigam, Suparnojit Sarkar, Piyush PatelMultilingual Language Models Healthcare
University of Birmingham, Dubai, United Arab Emirates · Heritage Institute of Technology, Kolkata, India · Madan Mohan Malaviya University of Technology, India
Large Language Models Lack Temporal Awareness of Medical Knowledge
May 13, 2026Zihan Guan, Qiao Jin, Guangzhi Xiong +6Healthcare Temporal Reasoning in Language Models
University of Virginia · National Institutes of Health · Dana-Farber Cancer Institute +2
Training Large Language Models to Predict Clinical Events
May 12, 2026Benjamin Turtel, Paul Wilczewski, Kris SkotheimHealthcare Language Model Calibration
Lightning Rod Labs
To Whom Do Language Models Align? Measuring Principal Hierarchies Under High-Stakes Competing Demands
May 12, 2026Fangyi Yu, Nabeel Seedat, Jonathan Richard Schwarz +1LLM Alignment Language Model Safety Evaluation
Thomson Reuters Foundational Research, 5 Canada Square, London · Imperial College London · University of Oxford
AcuityBench: Evaluating Clinical Acuity Identification and Uncertainty Alignment
May 12, 2026Robin Linzmayer, Georgianna Lin, Di Coneybeare +22Healthcare Clinical Triage
Department of Computer Science, Columbia University · Department of Biomedical Informatics, Columbia University · Department of Computer Science, Columbia University, New York, NY, USA +3
Medical Incident Causal Factors and Preventive Measures Generation Using Tag-based Example Selection in Few-shot Learning
May 11, 2026Yuna Haseyama, Tomoki Ito, Hiroki Sakaji +1Healthcare Few-Shot Learning
Graduate School of Information Science and Technology Hokkaido University Hokkaido, Japan · National Institute of Information and Communications Technology (NICT) Kyoto, Japan · Faculty of Information Science and Technology Hokkaido University Hokkaido, Japan
CLR-voyance: Reinforcing Open-Ended Reasoning for Inpatient Clinical Decision Support with Outcome-Aware Rubrics
May 10, 2026Aishik Nagar, Arun-Kumar Kaliya-Perumal, Yu-Hsuan Han +5Healthcare Clinical Decision Support
ASUS Intelligent Cloud Services (AICS) · Rehabilitation Research Institute of Singapore, Nanyang Technological University · Department of Family Medicine,2026 Taipei Veterans General Hospital +2
Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Care
May 8, 2026Burcu Sayin, Ngoc Vo Hong, Ipek Baris Schlicht +8Healthcare Clinical Decision Support
Department of Information Engineering and Computer Science, University of Trento, Italy · Department of Medicine, Azienda Sanitaria Universitaria Integrata del Trentino (ASUIT), Trento, Italy · Universitat Politècnica de València, Spain +2
Can Language Models Identify Side Effects of Breast Cancer Radiation Treatments?
May 8, 2026Natalie Seah, Danielle S. Bitterman, Daphna Spiegel +1Breast Cancer Healthcare
University of Virginia · Mass General Brigham, Dana-Farber Cancer Institute, Harvard Medical School
MedAction: Towards Active Multi-turn Clinical Diagnostic LLMs
May 8, 2026Hsin-Ling Hsu, Zizheng Wang, Donghua Zhang +9Healthcare Medical Diagnosis
1National Chengchi University · 2Georgetown University · University of Michigan +3
Research on Security Enhancement Methods for Adversarial Robust Large Language Model Intelligent Agents for Medical Decision-Making Tasks
May 7, 2026Saisai HuClinical Decision Support LLM Agent Security
Pace University · New York, NY 10038 · United States
Automated Clinical Report Generation for Remote Cognitive Remediation: Comparing Knowledge-Engineered Templates and LLMs in Low-Resource Settings
May 7, 2026Yongxin Zhou, Fabien Ringeval, François PortetMedical Report Generation Clinical Language Model Evaluation
Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG, 38000 Grenoble, France
Eliciting associations between clinical variables from LLMs via comparison questions across populations
May 7, 2026Fabian Kabus, Kian Kordtomeikel, Thomas Brox +3LLM Interpretability Causal Structure Learning
Institute of Medical Biometry and Statistics (IMBI), Medical Center, University of Freiburg · Department of Computer Science, Faculty of Engineering, University of Freiburg · Department of Neurology and Neurophysiology, Medical Center, University of Freiburg +1
Decodable but Not Corrected by Fixed Residual-Stream Linear Steering: Evidence from Medical LLM Failure Regimes
May 7, 2026Ming LiuLanguage Model Steering Medical LLMs
Amazon
MedFabric and EtHER: A Data-Centric Framework for Word-Level Fabrication Generation and Detection in Medical LLMs
May 5, 2026Tung Sum Thomas Kwok, Qian Qian, Xiaofeng Lin +8Healthcare Hallucination Detection
University of California, Los Angeles CA 90095, USA · Optum AI, USA
CuraView: A Multi-Agent Framework for Medical Hallucination Detection with GraphRAG-Enhanced Knowledge Verification
May 5, 2026Severin Ye, Xiao Kong, Xiaopeng He +2Healthcare Hallucination Detection
School of Computer Science and Engineering Kyungpook National University Daegu, Republic of Korea · School of Airspace Science and Engineering Shandong University Weihai, China · Department of English Language and Literature, Kyungpook National University, Daegu, Republic of Korea
Reliability-Oriented Multilingual Orthopedic Diagnosis: A Domain-Adaptive Modeling and a Conceptual Validation Framework
May 4, 2026Danish Ali, Li Xiaojian, Sundas Iqbal +1Multilingual Language Model Evaluation Healthcare
School of Computer Science, Wuhan University, China · School of Software, Nanjing University of Information Science and Technology (NUIST), China · Department of Orthopedic, Bahawal Victoria Hospital, Pakistan
ReMedi: Reasoner for Medical Clinical Prediction
May 2, 2026Yushi Cao, Yiming Chen, Hongchao Jiang +2Fine-Tuning Clinical Outcome Prediction
ASUS Intelligent Cloud Services (AICS), Singapore · NTU Artificial Intelligence Center of Research Excellence (NTU AI-CoRE), Taiwan · National University of Singapore, Singapore
Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks
May 2, 2026Benjamin Warner, Ratna Sagari Grandhi, Max Kieffer +32LLM Evaluation Healthcare
Sophont · MedARC · Prime Intellect
Teaching LLMs Brazilian Healthcare: Injecting Knowledge from Official Clinical Guidelines
May 1, 2026Hugo Abonizio, Filipe Rocha Lopes, Roberto Lotufo +1Knowledge Augmentation for Language Models Healthcare
FEEC, UNICAMP, Campinas, Brazil · NoHarm.ai, Brazil · Maritaca AI, Brazil
CLEAR: Revealing How Noise and Ambiguity Degrade Reliability in LLMs for Medicine
May 1, 2026Kevin H. Guo, Chao Yan, Avinash Baidya +5Healthcare LLM Reliability
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA · Intuit AI Research, Mountain View, CA, USA · Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA +2

May 19, 2026, cs.CLJ/K move · Enter open · S save

Synthesis and Evaluation of Long-term History-aware Medical Dialogue

Hebin Hu, Renke Dai, Ah-Hwee Tan, Yilin Kang

South-Central Minzu University Wuhan, China · Singapore Management University Singapore, Singapore

Healthcare AI Agent Benchmarks Long-Term Conversational Memory Synthetic Data Generation for Language Models Medical LLMs Text Generation

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An effective healthcare agent must be able to recall and reason over a patient's longitudinal medical history. However, the absence of datasets with realistic long-term dialogue timelines limits systematic evaluation. Real clinical text is constrained by privacy and ethics, while existing benchmarks focus on isolated interactions, failing to capture cross-session reasoning. We introduce a framework for synthesizing high-quality, long-term medical dialogues with LLMs. Our approach entails a knowledge-guided decomposition into three stages: constructing synthetic patient profiles with diverse disease and complication trajectories, generating multi-turn dialogues per encounter, and integrating them into a coherent longitudinal history dataset, MediLongChat. We establish three benchmark tasks-In-dialogue Reasoning, Cross-dialogue Reasoning, and Synthesis Reasoning-to evaluate the memory capabilities of healthcare agents. To assess data quality, we introduce a multi-dimensional evaluation framework combining vector-based metrics with LLM-as-a-judge assessments. Specifically, we define automatic measures-Faithfulness, Coherence, and Diversity-together with two LLM-based evaluations: Correctness and Realism. Benchmark experiments show that even state-of-the-art LLMs struggle with MediLongChat. These findings highlight the benchmark's applicability and underscore the need for tailored methods to advance healthcare agents.

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Latest papers 238