Clinical decision support systems combine knowledge and data from a variety of sources, represented by quantitative models based on stochastic methods, or qualitative based rather on expert heuristics and deductive reasoning. At the same time, case-based reasoning (CBR) memorizes and returns the experience of solving similar problems. The cooperation of heterogeneous clinical knowledge bases (knowledge objects, semantic distances, evaluation functions, logical rules, databases...) is based on medical ontologies. A multi-agent decision support system (MADSS) enables the integration and cooperation of agents specialized in different fields of knowledge (semiology, pharmacology, clinical cases, etc.). Each specialist agent operates a knowledge base defining the conduct to be maintained in conformity with the state of the art associated with an ontological basis that expresses the semantic relationships between the terms of the domain in question. Our approach is based on the specialization of agents adapted to the knowledge models used during the clinical steps and ontologies. This modular approach is suitable for the realization of MADSS in many areas.
Toward Vibe Medicine: A Self-Evolving Multi-Agent Framework for Clinical Decision Support
Medical AI Lab, The First Hospital of Hebei Medical University（河北医科大学第一医院医学人工智能实验室）；Hebei Provincial Engineering Research Center for AI-Based Cancer Treatment Decision-Making, The First Hospital of Hebei Medical University（河北省人工智能癌症治疗决策工程研究中心，河北医科大学第一医院）；State Key Laboratory of Neurology and Oncology Drug Development（神经与肿瘤药物研发国家重点实验室）；School of Computing, University of Georgia（佐治亚大学计算学院）；Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College（中国医学科学院北京协和医学院国家癌症中心/国家肿瘤临床医学研究中心/肿瘤医院深圳医院放射治疗科）；Department of Radiation Oncology, Mayo Clinic（梅奥诊所放射肿瘤科）；College of Mechanical and Power Engineering, China Three Gorges University（三峡大学机械与动力工程学院）；Department of Radiation Oncology, Guangzhou Concord Cancer Center（广州康华肿瘤中心放射治疗科）；Gastrointestinal Disease Diagnosis and Treatment Center, The First Hospital of Hebei Medical University（河北医科大学第一医院胃肠疾病诊疗中心）；Department of General Surgery, The First Hospital of Hebei Medical University（河北医科大学第一医院普通外科）
Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology
FOM University of Applied Sciences（FOM应用科技大学）；University Hospital Düsseldorf（杜塞尔多夫大学医院）；Heinrich-Heine-University（海因里希·海涅大学）；Hiller Research Center（希勒研究中心）；KEM Kliniken Essen-Mitte（埃森中部KEM医院）
Integrating Causal Machine Learning into Clinical Decision Support Systems: Insights from Literature and Practice
University of Bayreuth and Fraunhofer FIT（拜罗伊特大学和弗劳恩霍夫 FIT 研究所）；Technical University of Munich（慕尼黑技术大学）；Wharton School, University of Pennsylvania（宾夕法尼亚大学沃顿商学院）
From Retrieving Information to Reasoning with AI: Exploring Different Interaction Modalities to Support Human-AI Coordination in Clinical Decision-Making
Stanford University Palo Alto CA USA；Joseph Brant Hospital \& Foundation Ontario ON Canada；Stanford University；Joseph Brant Hospital \& Foundation
Assessing the communication gap between AI models and healthcare professionals: explainability, utility and trust in AI-driven clinical decision-making
The University of Manchester（曼彻斯特大学）；CRUK Manchester Institute（英国癌症研究中心曼彻斯特研究所）；Idiap Research Institute（Idiap研究所）
A Governance and Evaluation Framework for Deterministic, Rule-Based Clinical Decision Support in Empiric Antibiotic Prescribing
Grupo de Bioingeniería y Telemedicina, ETSI Telecomunicación, Centro de Tecnología Biomedica, Universidad Politécnica de Madrid（生物工程与电信学院，生物医学技术中心，马德里理工大学）；Instituto de Investigación Hospital 12 de Octubre (imas12), Hospital Universitario 12 de Octubre（12月12日医院研究所（imas12），12月12日大学医院）；Innovation Unit, Parc Sanitari Sant Joan de Deu（创新单元，圣约翰德德乌卫生公园）；Infectious Diseases Department, Parc Sanitari Sant Joan de Deu（感染性疾病部门，圣约翰德德乌卫生公园）；Centro de Investigación Biomédica en Red, Biomateriales y Nanomedicina (CIBER-BBN)（生物医学研究网络，生物材料与纳米医学（CIBER-BBN））
MedGuideX: Internalizing Decision Logic from Executable Guidelines into Large Language Models for Clinical Reasoning
University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Albert Einstein College of Medicine（爱因斯坦医学院）
Retrieval-Augmented Framework for LLM-Based Clinical Decision Support
Dept. of Computer Science, The University of Texas at El Paso, USA（计算机科学系，德克萨斯大学埃尔帕索分校）；Dept. of Emergency Medicine, University of Maryland School of Medicine, USA（急诊医学系，马里兰大学医学院）；Dept. of Public Health Sciences, The University of Texas at El Paso, USA（公共卫生科学系，德克萨斯大学埃尔帕索分校）
ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models
East China University of Science and Technology, Shanghai, China（东华大学）；Renji Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China（复旦大学附属中山医院）
Developing Large Language Models for Clinical Research Using One Million Clinical Trials
Usher Institute, Edinburgh Medical School, University of Edinburgh（埃丁堡大学埃丁堡医学院usher研究所）；Health Data Research UK（英国健康数据研究）；School of Computing and Data Science, University of Illinois Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校计算与数据科学学院）；Division of Intramural Research, National Library of Medicine, National Institutes of Health（国家卫生研究院国家医学图书馆内部研究部）；Keiji AI
Beyond MedQA: Towards Real-world Clinical Decision Making in the Era of LLMs
Department of Computer Science, Emory University（埃默里大学计算机科学系）；Children’s Healthcare of Atlanta（亚特兰大儿童医院）；Nell Hodgson Woodruff School of Nursing, Emory University（埃默里大学奈尔·霍德森·伍德鲁夫护理学院）
