arXivDaily arXiv每日学术速递 周一至周五更新

科学与医疗

医学 AI

医学智能、临床 AI、医学影像、病理、诊断和医疗健康大模型。

共收录 951 信号源:cs.CV, cs.LG, q-bio, eess.IV, eess.SP

1. 临床大模型 951 篇

2508.08270 2025-12-30 cs.LG cs.AI cs.CL cs.MM 90%

Doctor Sun: A Bilingual Multimodal Large Language Model for Biomedical AI

Doctor Sun: 一种双语多模态大语言模型用于生物医学AI

Dong Xue, Ziyao Shao, Zhaoyang Duan, Fangzhou Liu, Bing Li, Zhongheng Zhang

机构 * Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education East China University of Science and Technology(能源化工过程智能制造重点实验室,东华大学) Research Institute of Intelligent Control and Systems Harbin Institute of Technology(智能控制与系统研究室,哈尔滨工业大学) Department of Emergency Medicine, Sir Run Run Shaw Hospital Zhejiang University School of Medicine(浙江大学医学院急诊医学科) Provincial Key Laboratory of Precise Diagnosis Treatment of Abdominal Infection, Sir Run Run Shaw Hospital Zhejiang University School of Medicine(腹部感染精准诊断治疗省级重点实验室,浙江大学医学院) School of Medicine Shaoxing University(绍兴大学医学院)

专题命中 临床大模型 :medical AI(title,abstract);biomedical(title,abstract);pathology(abstract);radiology(abstract)

AI总结 Doctor Sun是一种双语多模态大语言模型,通过整合预训练视觉编码器和医学LLM,提升生物医学多模态任务的性能,并提供SunMed-VL数据集支持研究进展。

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2605.30646 2026-06-01 cs.CL cs.AI 83%

Same Patient, Different Words, Different Diagnosis? Evaluating Semantic Stability in Clinical LLMs

同一患者,不同措辞,不同诊断?评估临床大语言模型中的语义稳定性

Mahdi Alkaeed, Adnan Qayyum, Nabeel Abo Kashreef, Muhammad Bilal, Junaid Qadir

机构 * Department of Computer Science and Engineering, College of Engineering, Qatar University(卡塔尔大学计算机科学与工程系) College of Science and Engineering, Hamad Bin Khalifa University (HBKU)(哈马德·本·卡伊夫大学(HBKU)理学院) Primary Health Care Corporation (PHCC)(初级卫生保健公司) Birmingham City University(伯明翰城市大学)

专题命中 临床大模型 :clinical LLM(title);diagnosis(title)

AI总结 针对临床大语言模型对语义等价但措辞不同的提示敏感的问题,提出基于自然语言推理的语义验证框架和三个量化指标,评估16个开源通用与医学模型,发现领域专业化并不一致地提升或降低鲁棒性。

Comments 14 pages, 5 figures

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2608.09861 2026-08-11 cs.AI cs.CL cs.CV 新提交 83%

Towards Expert-level Medical AI for Real-time Video Consultations

面向专家级的实时视频问诊医疗AI

Mahvish Nagda, Jihyeon Lee, Matthew Thompson, Chunjong Park, Tim Strother, Valentin Liévin, Roma Ruparel, Akshay Goel, Teya Bergamaschi, Suhana Bedi, Meet Shah, Pavel Dubov, Liviu Panait, Toshiyuki Fukuzawa, Sam Schmidgall, Craig Schiff, Joseph Xu, Aliya Rysbek, Yana Lunts, Jan Freyberg, Rebecca Hemengway, Sunny Virmani, David Racz, Carey Radebaugh, Joëlle Barral, Kavi Goel, Dale R. Webster, Katherine Chou, Avinatan Hassidim, Yossi Matias, James Manyika, Gregory Wayne, Tao Tu, Yun Liu, Ethan Goh, Christina Chen, Ryutaro Tanno, Po-Hsuan Cameron Chen, Mike Schaekermann, Anil Palepu

机构 * Google Research(谷歌研究院) Google DeepMind(谷歌DeepMind)

专题命中 临床大模型 :medical AI(title,abstract);diagnosis(abstract);分类 cs.CV

AI总结 本研究开发了基于Gemini的多智能体系统AMIE(视频版),在随机OSCE研究中其临床问诊表现与初级保健医生相当或更优,为专家级实时视频问诊医疗AI的发展奠定了重要基础。

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2603.13743 2026-03-17 cs.CY 82%

Six Interventions for the Responsible and Ethical Implementation of Medical AI Agents

为医疗AI代理的负责任和伦理实施提出的六种干预措施

Tom Bisson, Henriette Voelker, Sanddhya Jayabalan, A John Iafrate, Jakob N Kather, Jochen K Lennerz

专题命中 临床大模型 :medical AI(title,abstract);clinical AI(abstract)

AI总结 本文提出六种干预措施,旨在通过伦理设计框架确保医疗AI代理在自主系统中维持医疗伦理核心原则。

Comments 7 pages, 1 figure

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2410.00174 2025-06-18 cs.HC 82%

Why Interdisciplinary Teams Fail: A Systematic Analysis With Activity Theory in Clinical AI Collaboration

Bingsheng Yao, Yao Du, Yue Fu, Xuhai Xu, Yanjun Gao, Hong Yu, Dakuo Wang

专题命中 临床大模型 :clinical AI(title,abstract);pathology(abstract)

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2201.04631 2022-01-14 eess.IV cs.CV 81%

Early Diagnosis of Parkinsons Disease by Analyzing Magnetic Resonance Imaging Brain Scans and Patient Characteristics

Sabrina Zhu

专题命中 临床大模型 :diagnosis(title);MRI(abstract);分类 cs.CV、eess.IV

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2111.11665 2021-11-30 eess.IV cs.CV 81%

RadFusion: Benchmarking Performance and Fairness for Multimodal Pulmonary Embolism Detection from CT and EHR

Yuyin Zhou, Shih-Cheng Huang, Jason Alan Fries, Alaa Youssef, Timothy J. Amrhein, Marcello Chang, Imon Banerjee, Daniel Rubin, Lei Xing, Nigam Shah, Matthew P. Lungren

专题命中 临床大模型 :CT(title,abstract);分类 cs.CV、eess.IV

Comments RadFusion dataset: https://stanfordaimi.azurewebsites.net/datasets/3a7548a4-8f65-4ab7-85fa-3d68c9efc1bd

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2506.17442 2026-02-05 cs.AI cs.ET cs.LG 80%

Keeping Medical AI Healthy and Trustworthy: A Review of Detection and Correction Methods for System Degradation

保持医疗AI的健康与可信:对系统退化检测与纠正方法的综述

Hao Guan, David Bates, Li Zhou

专题命中 临床大模型 :medical AI(title,abstract);分类 cs.LG;biomedical(journal_ref)

AI总结 本文综述了医疗AI系统退化检测与纠正方法,探讨了性能退化原因、检测技术、根本原因分析及纠正策略,旨在提升医疗AI的可靠性和安全性。

Comments 16 pages, 5 figures

Journal ref IEEE Transactions on Biomedical Engineering, 2026

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2004.09338 2020-04-30 cs.LG cs.IR q-bio.QM 80%

Augmented Curation of Unstructured Clinical Notes from a Massive EHR System Reveals Specific Phenotypic Signature of Impending COVID-19 Diagnosis

FNU Shweta, Karthik Murugadoss, Samir Awasthi, AJ Venkatakrishnan, Arjun Puranik, Martin Kang, Brian W. Pickering, John C. O'Horo, Philippe R. Bauer, Raymund R. Razonable, Paschalis Vergidis, Zelalem Temesgen, Stacey Rizza, Maryam Mahmood, Walter R. Wilson, Douglas Challener, Praveen Anand, Matt Liebers, Zainab Doctor, Eli Silvert, Hugo Solomon, Tyler Wagner, Gregory J. Gores, Amy W. Williams, John Halamka, Venky Soundararajan, Andrew D. Badley

专题命中 临床大模型 :diagnosis(title,abstract);分类 cs.LG、q-bio

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2608.04180 2026-08-06 cs.LG 新提交 79%

A Comparative Study of Feature Selection Methods for EHR Diagnosis Codes in Opioid Use Disorder Prediction

阿片类药物使用障碍预测中用于电子健康记录诊断代码的特征选择方法对比研究

Zihan Ding, Yinan Liu, Tengfei Ma, Rachel Wong, George Leibowitz, Benjamin Littenberg, Xia Zheng, Richard N. Rosenthal, Fusheng Wang

机构 * Stony Brook University(石溪大学) Rutgers University(罗格斯大学) University of Vermont(佛蒙特大学)

专题命中 临床大模型 :diagnosis(title,abstract);分类 cs.LG

AI总结 本研究对比五种特征选择方法在阿片类药物使用障碍预测中的表现,发现NTK敏感性方法在准确性与稳定性间平衡最优,LLM引导选择可提供互补临床信号。

Comments Accepted at the AMIA 2026 Annual Symposium

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2604.28010 2026-05-19 cs.LG cs.AI 79%

Learning from Disagreement: Clinician Overrides as Implicit Preference Signals for Clinical AI in Value-Based Care

从分歧中学习:临床医生的覆盖作为价值医疗中临床AI的隐含偏好信号

Prabhjot Singh, Abhishek Gupta, Chris Betz, Abe Flansburg, Brett Ives, Sudeep Lama, Jung Hoon Son

机构 * Altitude

专题命中 临床大模型 :clinical AI(title,abstract);分类 cs.LG

AI总结 本文提出了一种框架,将临床医生对AI建议的覆盖视为隐含偏好数据,通过引入五类覆盖分类法和双学习架构,解决抑制偏差问题,以提升价值医疗中AI的决策能力。

Comments 22 pages, 2 tables, 1 figure

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2603.17248 2026-03-19 cs.LG cs.AI 79%

Pathology-Aware Multi-View Contrastive Learning for Patient-Independent ECG Reconstruction

考虑病理的多视图对比学习用于患者无关的ECG重建

Youssef Youssef, Jitin Singla

机构 * Department of Computer Science and Engineering, Indian Institute of Technology Roorkee(计算机科学与工程系,印度理工学院Roorkee) Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee(生物科学与生物工程系,印度理工学院Roorkee)

专题命中 临床大模型 :pathology(title,abstract);分类 cs.LG

AI总结 本文提出考虑病理的多视图对比学习框架,通过病理 manifold 正则化潜在空间,结合高保真时间域波形与病理感知嵌入,减少解剖噪声,实现患者无关的ECG重建。

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2603.02367 2026-03-04 cs.CV 79%

Retrieving Patient-Specific Radiomic Feature Sets for Transparent Knee MRI Assessment

为透明膝关节MRI评估检索患者特异性放射组学特征集

Yaxi Chen, Simin Ni, Jingjing Zhang, Shaheer U. Saeed, Yipei Wang, Aleksandra Ivanova, Rikin Hargunani, Chaozong Liu, Jie Huang, Yipeng Hu

机构 * Mechanical Engineering Department, University College London, London, UK Hawkes Institute, University College London, London, UK Institute of Orthopaedic \& Musculoskeletal Science, University College London, Royal National Orthopaedic Hospital, Stanmore, UK School of Engineering Materials Science, Queen Mary University of London, London, UK Centre for Bioengineering, Queen Mary University of London, London, UK Department of Medical Physics Biomedical Engineering, University College London, London, UK Royal National Orthopaedic Hospital, Stanmore, UK

专题命中 临床大模型 :MRI(title);diagnosis(abstract);分类 cs.CV

AI总结 本文提出了一种患者特异性特征集选择框架,通过两阶段检索策略提升膝关节MRI评估的透明性和诊断性能。

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2504.20741 2026-02-06 cs.HC cs.AI cs.CY cs.LG 79%

In defence of post-hoc explanations in medical AI

为医疗AI中的事后解释辩护

Joshua Hatherley, Lauritz Munch, Jens Christian Bjerring

机构 * Center for the Philosophy of AI(哲学人工智能中心) University of Copenhagen(哥本哈根大学) Department of Philosophy and History of Ideas(哲学与思想史系) Aarhus University(奥胡斯大学)

专题命中 临床大模型 :medical AI(title,abstract);分类 cs.LG

AI总结 本文为医疗AI中的事后解释辩护,指出其虽无法完全复制黑盒推理过程,但能提升用户理解、提高临床团队准确性并辅助医生决策。

Journal ref 2026. Hastings Center Report 56(1): 40-46

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2401.11648 2024-05-02 cs.LG cs.AI cs.IR 79%

Next Visit Diagnosis Prediction via Medical Code-Centric Multimodal Contrastive EHR Modelling with Hierarchical Regularisation

Heejoon Koo

专题命中 临床大模型 :diagnosis(title,abstract);分类 cs.LG

Comments Accepted to EACL 2024 (The 18th Conference of the European Chapter of the Association for Computational Linguistics)

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2302.10180 2023-02-22 cs.LG 79%

Diagnosis of Covid-19 Via Patient Breath Data Using Artificial Intelligence

Ozge Doguc, Gokhan Silahtaroglu, Zehra Nur Canbolat, Kailash Hambarde, Ahmet Alperen Yigitbas, Hasan Gokay, Mesut Ylmaz

专题命中 临床大模型 :diagnosis(title,abstract);分类 cs.LG

Comments 9

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2201.10650 2022-01-27 cs.CV cs.AI 79%

Beyond Visual Image: Automated Diagnosis of Pigmented Skin Lesions Combining Clinical Image Features with Patient Data

José G. M. Esgario, Renato A. Krohling

专题命中 临床大模型 :diagnosis(title,abstract);分类 cs.CV

Comments 33 pages, 11 figures

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2111.08168 2021-11-17 cs.LG cs.AI 79%

Explaining medical AI performance disparities across sites with confounder Shapley value analysis

Eric Wu, Kevin Wu, James Zou

专题命中 临床大模型 :medical AI(title,abstract);分类 cs.LG

Comments Machine Learning for Health (ML4H) - Extended Abstract

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2004.04645 2021-03-03 cs.LG stat.ML 79%

Query-Focused EHR Summarization to Aid Imaging Diagnosis

Denis Jered McInerney, Borna Dabiri, Anne-Sophie Touret, Geoffrey Young, Jan-Willem van de Meent, Byron C. Wallace

专题命中 临床大模型 :diagnosis(title,abstract);分类 cs.LG

Journal ref Proceedings of Machine Learning Research 126 (2020) 632-659

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2006.16926 2021-02-23 cs.CY cs.CL cs.LG 79%

A Deep Learning Pipeline for Patient Diagnosis Prediction Using Electronic Health Records

Leopold Franz, Yash Raj Shrestha, Bibek Paudel

专题命中 临床大模型 :diagnosis(title,abstract);分类 cs.LG

Journal ref BIOKDD 2020 at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2020

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2604.08226 2026-04-10 cs.AI cs.HC cs.SY eess.SY 79%

Grounding Clinical AI Competency in Human Cognition Through the Clinical World Model and Skill-Mix Framework

通过临床世界模型和技能混合框架在人类认知中奠定临床AI能力

Seyed Amir Ahmad Safavi-Naini, Elahe Meftah, Josh Mohess, Pooya Mohammadi Kazaj, Georgios Siontis, Zahra Atf, Peter R. Lewis, Mauricio Reyes, Girish Nadkarni, Roland Wiest, Stephan Windecker, Christoph Grani, Ali Soroush, Isaac Shiri

机构 * Department of Cardiology, Inselspital, Bern University Hospital, University of Bern(伯尔尼大学医院心脏病学系,伯尔尼大学) Department of Digital Medicine, Bern University Hospital, University of Bern(伯尔尼大学医院数字医学系,伯尔尼大学) Division of Data-Driven and Digital Medicine (D3M), Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院数据驱动与数字医学部) Clinical Research Development Center, Amir Oncology Teaching Hospital, Shiraz University of Medical Sciences(设拉子医科大学阿米尔肿瘤教学医院临床研究发展中心) Graduate School for Cellular and Biomedical Sciences, University of Bern(伯尔尼大学细胞与生物医学研究生院) Faculty of Business and Information Technology, Ontario Tech University(安大略理工大学商业与信息技术学院) Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern(伯尔尼大学医院放射肿瘤学系,伯尔尼大学) ARTORG Center for Biomedical Engineering Research, University of Bern(伯尔尼大学ARTORG生物医学工程研究中心) The Charles Bronfman Institute of Personalised Medicine, Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院查尔斯·布朗夫曼个性化医学研究所) University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern(伯尔尼大学医院诊断与介入神经放射学大学研究所,伯尔尼大学) Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine(瑞士转化与创业医学研究所转化影像中心) Henry D. Janowitz Division of Gastroenterology, Icahn School of Medicine at Mount Sinai(西奈山伊坎医学院亨利·D·雅诺维茨消化内科)

专题命中 临床大模型 :clinical AI(title,abstract)

AI总结 本文提出临床世界模型和技能混合框架,通过八维定义临床能力空间,为AI在医疗场景中的能力评估和验证提供结构化方法。

Comments Code, data (Clinical AI Skill-Mix dimension specifications), and an exploratory dashboard are available at https://github.com/Sdamirsa/Clinical-World-Model

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2601.06161 2026-01-13 cs.AI 79%

Beyond Accuracy: A Decision-Theoretic Framework for Allocation-Aware Healthcare AI

超越准确度:一种面向资源分配的医疗AI决策理论框架

Rifa Ferzana

专题命中 临床大模型 :healthcare AI(title,abstract)

AI总结 本文提出一种决策理论框架,用于在资源受限条件下优化医疗AI的分配策略,通过约束优化和马尔可夫决策过程,展示改进的估计如何影响最优分配。

Comments 11 pages, 3 figures, PDF-only submission. This work introduces a decision-theoretic framework to bridge the gap between predictive accuracy and clinical impact in healthcare AI. Includes synthetic simulation results

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2311.16197 2023-11-29 eess.IV cs.AI cs.LG 79%

Generation of patient specific cardiac chamber models using generative neural networks under a Bayesian framework for electroanatomical mapping

Sunil Mathew, Jasbir Sra, Daniel B. Rowe

专题命中 临床大模型 :MRI(abstract);CT(abstract);diagnosis(abstract);分类 cs.LG、eess.IV

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2607.24793 2026-07-29 cs.IR cs.CL 新提交 78%

Retrieval, not hallucinations, will be the limiting factor for LLM-based clinical AI tools

检索而非幻觉将成为基于大语言模型的临床人工智能工具的限制因素

Kirk Roberts, Steven Bedrick, Kurt Miller, William R. Hersh, Hongfang Liu

专题命中 临床大模型 :clinical AI(title,abstract)

AI总结 探讨临床人工智能中基于大语言模型的错误,将讨论重点从精度错误转向召回错误,特别是患者级数据检索方面,概述错误类型、缓解策略及研究方向,提供检索评估概述。

Comments Perspective piece

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2607.20848 2026-07-24 cs.AI 新提交 78%

Auditing Evidence Use in Medical LLM Diagnosis

医学大语言模型诊断中证据使用的审计

Junchi Liao, Jiawen Deng, Fuji Ren

机构 * University of Electronic Science and Technology of China(电子科技大学)

专题命中 临床大模型 :diagnosis(title,abstract)

AI总结 研究医学大语言模型诊断时证据使用情况,通过分解患者信息为证据单元等方法审计,在多个数据集上评估五个模型,发现准确性可能掩盖证据使用问题,结果促使对医学大语言模型评估进行角色感知审计。

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2607.18086 2026-07-21 cs.AI 新提交 78%

Judge-dependent safety gains and model-specific helpfulness costs of evidence-sufficiency prompting in clinical LLMs

临床大语言模型中证据充分性提示的依赖判断的安全增益和特定模型的有用性成本

Koyar Afrasyab

专题命中 临床大模型 :clinical LLM(title);diagnosis(abstract)

AI总结 研究临床大语言模型中证据充分性提示的安全增益及有用性成本,通过在公共数据基准中让四个模型用标准提示和包装器回答问题,发现安全增益有方向和幅度差异且依赖评判者,同时存在模型特定的有用性成本。

Comments https://github.com/KAVentures/clinical-evidence-sufficiency-llm

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2602.01086 2026-07-17 cs.AI cs.CR cs.DB cs.DC cs.SE 版本更新 78%

MedBeads: An AI-Native Clinical Context Graph Built from Immutable Beads and Reconstructable Clinical Links

MedBeads:面向可信医疗AI的智能体原生不可变数据基底

Takahito Nakajima

机构 * Diagnostic Imaging and Interventional Radiology, Institute of Medicine, University of Tsukuba(东京大学医学研究院诊断影像与介入放射学部) Center for Cyber Medicine Research, University of Tsukuba(东京大学计算机医学研究中心)

专题命中 临床大模型 :medical AI(title,abstract)

AI总结 针对医疗AI中电子病历与智能体间的上下文不匹配问题,提出基于Merkle有向无环图的不可变数据架构MedBeads,通过确定性图遍历替代概率检索,实现可审计、防篡改的临床上下文提供。

Comments 23 pages, 5 figures, 3 tables. Reference implementation and reproducible Docker demo available at https://github.com/medbeads/medbeads

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2602.11391 2026-07-08 cs.CL 版本更新 78%

A Patient Simulation Framework for Risk Assessment of Conversational Healthcare AI: Evaluation of an Antidepressant Decision Aid

通过患者模拟推进AI可信度:对抗抑郁药物选择的对话代理风险评估

Md Tanvir Rouf Shawon, Mohammad Sabik Irbaz, Hadeel R. A. Elyazori, Keerti Reddy Resapu, Yili Lin, Vladimir Franzuela Cardenas, K. Pierre Eklou, Farrokh Alemi, Kevin Lybarger

机构 * George Mason University (GMU)(乔治梅森大学)

专题命中 临床大模型 :healthcare AI(title);clinical AI(abstract)

AI总结 本文提出一个患者模拟器用于评估医疗对话代理的可扩展自动化评估,通过系统变化医疗、语言和行为维度支持风险评估。方法基于NIST AI风险管理框架,整合医疗、语言和行为三种profile,评估AI决策辅助在抗抑郁药物选择中的表现。

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2607.00990 2026-07-02 cs.SE cs.AI 新提交 78%

SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests

SWE-Doctor: 通过多面缺陷复现测试的运行时诊断引导软件工程智能体

Yaoqi Guo, Yang Liu, Jie M. Zhang, Yun Ma, Yiling Lou, Zhenpeng Chen

专题命中 临床大模型 :diagnosis(title,abstract)

AI总结 提出SWE-Doctor,通过生成多面缺陷复现测试并执行调试,构建运行时诊断记录,结合定位信息指导补丁生成,在SWE-bench Verified和Pro上平均解决率分别达75.7%和59.4%。

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2510.04033 2026-06-24 cs.AI 版本更新 78%

A global log for medical AI

医疗AI的全局日志

Ayush Noori, Aaron E. Boussina, Hai Ho Bich, James Anibal, Julia Maslinski, Manuel Burger, Martin Faltys, Adam Rodman, Alan Karthikesalingam, Alessandro Blasimme, Annelia Itwaru, Ben Kaplan, Bilal A. Mateen, Christopher A. Longhurst, Daniel Yang, Dave deBronkart, Effy Vayena, Fedor Sergeev, Gauden Galea, Ha Thi Hai Duong, Harold F. Wolf, Jacob Waxman, Joerg C. Schefold, Joshua C. Mandel, Juliana Rotich, Kenneth D. Mandl, Lily Poursoltan, Maryam Mustafa, Melissa Miles, Nigam H. Shah, Noa Dagan, Pavan Bodanki, Peter Lee, Philipp Koralus, Prathamesh Parchure, Prem Timsina, Ran D. Balicer, Robert Korom, Scott Mahoney, Seth Hain, Tien Yin Wong, Trevor Mundel, Vivek Natarajan, Ankit Sakhuja, Benjamin Glicksberg, C. Louise Thwaites, Gunnar Rätsch, Karandeep Singh, David A. Clifton, Isaac S. Kohane, Marinka Zitnik

机构 * Harvard Medical School(哈佛医学院) University of Oxford(牛津大学) Institute for Ethics in AI(人工智能伦理研究所) Cosmos Institute(宇宙研究所) Harvard Medical School and Clalit Research Institute(哈佛医学院和Clalit研究机构) University of California, San Diego(加州大学圣地亚哥分校) Joan and Irwin Jacobs Center for Health Innovation(乔安和伊万·雅各布健康创新中心) Oxford University Clinical Research Unit(牛津大学临床研究中心) Icahn School of Medicine at Mount Sinai(辛格纳医学中心) The Hasso Plattner Institute for Digital Health at Mount Sinai(辛格纳医学中心数字健康研究所) ETH Zurich(苏黎世联邦理工学院) University Hospital, University of Bern(伯恩大学医院) Beth Israel Deaconess Medical Center(贝斯以色列医疗中心) Google DeepMind(谷歌DeepMind) The Mount Sinai AI Assurance Lab(辛格纳医学中心人工智能保证实验室) University of Birmingham(伯明翰大学) PATH(PATH组织) Seattle Children’s Hospital(西雅图儿童医院) Department of Pediatrics, University of California, San Diego(加州大学圣地亚哥分校儿科部) Kaiser Foundation Health and Hospitals(凯撒基金会健康与医院) e-Patient Dave, LLC(e-Patient Dave公司) Regional Office for Europe, World Health Organization(世界卫生组织欧洲地区办公室) University of Malta(马耳他大学) Centre for Tropical Medicine and Global Health, University of Oxford(牛津大学热带医学与全球健康中心) Healthcare Information and Management Systems Society(医疗信息与管理系统协会) Clalit Research Institute, Innovation Division, Clalit Health Services(Clalit研究机构创新部门,Clalit健康服务) Microsoft Research(微软研究院) Gates Foundation(比尔及梅琳达·盖茨基金会) Computational Health Informatics Program, Boston Children’s Hospital(波士顿儿童医院计算健康信息学项目)

专题命中 临床大模型 :medical AI(title,abstract)

AI总结 提出MedLog协议,为医疗AI系统提供事件级日志记录,包含九个核心字段,并在多个部署中验证其监测模型行为、工作流交互及下游结果的能力。

Comments MedLog website: https://medlogprotocol.ai

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