Deep Learning Estimation of Forced Expiratory Volume in One Second/Forced Vital Capacity and Obstructive Lung Disease Classification From Chest Radiographs With Subgroup Performance Analysis in a North American Cohort: Retrospective Cohort Study [0.03%]
基于胸部X线片的深度学习估计一秒用力呼气容积/用力肺活量和阻塞性肺病分类：北美队列的回顾性队列研究及亚组性能分析
Eptehal Nashnoush,Helen D&#x;Couto,Benjamin Fine et al.
Eptehal Nashnoush et al.
Background: Spirometry is the standard physiological test defining airflow obstruction, the key criterion for diagnosing chronic obstructive pulmonary disease. It is underused in high-income settings and often unavailable...
Correctness, Harmfulness, and Diversity of Large Language Models for Colonoscopy Preparation Assistance: Comparative Evaluation Study [0.03%]
结肠镜检查准备辅助的大型语言模型的正确性、危害性和多样性的比较评价研究
Tomiris Kaumenova,Subhankar Chakraborty,Eric Fosler-Lussier et al.
Tomiris Kaumenova et al.
Background: Colorectal cancer is a leading cause of cancer-related deaths in the United States, and colonoscopy remains the gold standard for early detection and prevention. However, many procedures are postponed due to i...
Mapping the Evolving AI Preferences and Care Needs in Orthopedic Transitional Care From Hospitals to Home: Cross-Sectional Study [0.03%]
基于医院到家庭的骨科过渡护理中人工智能偏好的演变及照护需求地图绘制：横断面研究
Xiaomin Huang,Xiaoqiong Peng,Weiling Zhang et al.
Xiaomin Huang et al.
Background: Enhanced recovery after surgery protocols have shortened orthopedic hospital stays but have shifted rehabilitation and safety-monitoring tasks to patients and families after discharge. In this study, AI refers...
AI in Disaster Medicine: Scoping Review of Methods, Validation, and System Integration [0.03%]
人工智能在灾难医学中的应用：方法、验证及系统集成的综述性研究
Ruben Peralta,Ali Msheik,Zeinab Al Mokdad et al.
Ruben Peralta et al.
Background: AI is increasingly proposed as a tool to enhance disaster medicine through improved situational awareness, decision support, and resource coordination. However, the extent to which current research has progres...
Review
JMIR AI. 2026 Aug 4:5:e90848. DOI:10.2196/90848 2026
Benchmarking AI-Powered Translation of the EQ-5D-5L Patient-Reported Outcome Measure Using Automated Metrics: Comparative Evaluation Study [0.03%]
基于自动化指标的AI驱动EQ-5D-5L患者报告结果测量翻译评估研究基准测试
Himanshu Vashisht,Tomás Ward,Willie Muehlhausen
Himanshu Vashisht
Background: Patient-reported outcome measures (PROMs) are central to multinational clinical research, but high-quality translation and linguistic validation remain resource-intensive. AI-powered translation may accelerate...
From Static Outputs to Living Evidence: AI for Integrated Knowledge Translation in Canadian Health Research [0.03%]
从静态输出到活生生的证据：加拿大健康研究中的人工智能综合知识转化
Zack van Allen,Jayne Beselt,Jerry M Maniate et al.
Zack van Allen et al.
Integrated knowledge translation still relies on static reports, presentations, and manuscripts that cannot adapt to decision-makers' evolving questions. Retrieval-augmented large language models can add a secure, auditable conversational l...
Improving Clinical Validity in Synthetic Electronic Health Record Generation Using Best-of-N Sampling: Comparative Evaluation Study [0.03%]
基于最佳抽样法改进合成电子健康记录生成的临床有效性的比较性评价研究
Md Akmol Masud,Mahmud Hasan
Md Akmol Masud
Background: Synthetic electronic health record generation is limited not only by statistical fidelity but also by clinical validity. Records that appear statistically plausible may still violate hard structural, physiolog...
Measuring Consistency Between Large Language Models' Responses to Preventive Care Queries and Official US Preventive Services Task Force (USPSTF) Recommendations: Systematic Test Involving All USPSTF Preventive Care Topics via Simulated User Prompts [0.03%]
测量大型语言模型对预防性护理查询的响应与官方美国预防服务工作组（USPSTF）建议之间的一致性：通过模拟用户提示针对所有USPSTF预防性护理主题的系统测试
Tim Johnson,Wolfgang Gaissmaier
Tim Johnson
Background: Large language models (LLMs) have the potential to provide individualized preventive care guidance at scale. Research, however, has found mixed performance among a small set of LLMs queried about select preven...
Evidence Use and Identifier-Conditioned Prior Knowledge in Large Language Model Classification of Oncology Trials Assessed Through Progressive Content Removal and Counterfactual Testing: Comparative Analysis [0.03%]
基于逐步内容删除和反事实测试的大型语言模型在肿瘤试验分类中的证据使用和标识符条件先验知识的比较分析
Paul Windisch,Carole Koechli,Fabio Dennstädt et al.
Paul Windisch et al.
Background: Large language models (LLMs) can accurately classify biomedical documents, but strong benchmark performance does not establish that predictions are grounded in the supplied text. In biomedical literature tasks...
AI-Generated Personalized Visualization of the Safe Place in Virtual Reality vs Traditional Safe Place Imagery: Randomized Controlled Trial [0.03%]
基于虚拟现实的AI生成个性化安全地带可视化与传统安全地带意象的对照试验
Franziska Griessenauer,Franziska Pfannerstill,Thomas Probst
Franziska Griessenauer
Background: Relaxation techniques, such as the "safe place" imagery exercise, are simple and accessible strategies to cope with the negative effects of stress. While virtual reality (VR) has been applied in relaxation res...