Medical AI Agents

Latest papers

39 papers7 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

A Versatile AI Agent for Rare Disease Diagnosis and Risk Gene Prioritization
May 7, 2026Tianyu Liu, Wangjie Zheng, Rui Yang +12Rare Disease Diagnosis Medical AI Agents
Interdepartmental Program in Computational Biology and Bioinformatics, Yale University · Department of Biostatistics, Yale University · Broad Institute of MIT and Harvard +13
PhysicianBench: Evaluating LLM Agents in Real-World EHR Environments
May 4, 2026Ruoqi Liu, Imran Q. Mohiuddin, Austin J. Schoeffler +10AI Agent Benchmarks Electronic Health Records
Stanford University
Healthcare AI GYM for Medical Agents
May 1, 2026Minbyul JeongMedical LLMs RL for Tool Use
Upstage AI
RadAgent: A tool-using AI agent for stepwise interpretation of chest computed tomography
Apr 16, 2026Mélanie Roschewitz, Kenneth Styppa, Yitian Tao +10Tool-Using Vision-Language Agents Healthcare
Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland · ETH AI Center, Zurich, Switzerland · Department of Computer Science, ETH Zurich, Zurich, Switzerland +5
Evo-MedAgent: Beyond One-Shot Diagnosis with Agents That Remember, Reflect, and Improve
Apr 15, 2026Weixiang Shen, Bailiang Jian, Jun Li +6Medical AI Agents LLM Agent Self-Improvement
Technical University of Munich (TUM) · TUM University Hospital · LMU Munich +3
BAAI Cardiac Agent: An intelligent multimodal agent for automated reasoning and diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging
Apr 5, 2026Taiping Qu, Hongkai Zhang, Lantian Zhang +18Medical AI Agents Medical Diagnosis
Beijing Academy of Artificial Intelligence, No. 150 Chengfu Road, Haidian District, Beijing 100084, China · Department of Radiology, Beijing Anzhen Hospital, Beijing Institute of Heart, Lung & Vascular Diseases, Capital Medical University, 2 Anzhen Road, Beijing 100029, China · Department of MR, the First Affiliated Hospital, Henan Medical University, 88 Jiankang Road, Weihui 453100, China +2
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
Meissa: Multi-modal Medical Agentic Intelligence
Mar 9, 2026Yixiong Chen, Xinyi Bai, Yue Pan +2Medical AI Agents Medical LLMs
Johns Hopkins University, Baltimore, MD, USA · Cornell University, Ithaca, NY, USA
Which Tool Response Should I Trust? Tool-Expertise-Aware Chest X-ray Agent with Multimodal Agentic Learning
Feb 25, 2026Zheang Huai, Honglong Yang, Xiaomeng LiMedical AI Agents Tool-Using Vision-Language Agents
The Hong Kong University of Science and Technology, Kowloon, Hong Kong

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A Versatile AI Agent for Rare Disease Diagnosis and Risk Gene Prioritization

Tianyu Liu, Wangjie Zheng, Rui Yang, Benny Kai Guo Loo+11

Interdepartmental Program in Computational Biology and Bioinformatics, Yale University · Department of Biostatistics, Yale University · Broad Institute of MIT and Harvard+13

Rare Disease Diagnosis Medical AI Agents Clinical Decision Support Agentic AI

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Accurate and timely diagnosis is essential for effective treatment, particularly in the context of rare diseases. However, current diagnostic workflows often lead to prolonged assessment times and low accuracy. To address these limitations, we introduce Hygieia, a multi-modal AI agent system designed to support precision disease diagnosis by integrating diverse data sources, including phenotypic features, genetic profiles, and clinical records. Hygieia features a router-based and knowledge-enhanced framework that mitigates hallucination and tailors diagnostic strategies to different disease categories. Notably, it prioritizes risk-related genomic factors for rare diseases and provides confidence scores to assist clinical decision-making. We conducted a comprehensive evaluation demonstrating that Hygieia achieves state-of-the-art performance across multiple diagnostic benchmarks. In collaboration with clinical experts from Yale School of Medicine and Duke-NUS Medical School, we further validated its practical utility by showing (1) Hygieia's superior diagnostic performance compared to physicians with an improvement from 12%-60% and (2) its effectiveness in assisting clinicians with medical records for handling real-world cases. Our findings indicate that Hygieia not only enhances diagnostic accuracy and interpretability but also significantly reduces clinician workload, highlighting its potential as a valuable tool in clinical decision support systems.