Multimodal GPT-5 for Predicting Poor Functional Outcomes After Intracerebral Hemorrhage in the Emergency Department: Validation Study [0.03%]
多模态GPT-5预测急诊科脑出血后功能预后的验证研究
Koutarou Matsumoto,Kazuaki Ishihara,Ryota Tamba et al.
Koutarou Matsumoto et al.
Background: In the emergency department, rapid prognostic assessment of patients with intracerebral hemorrhage (ICH) is essential for guiding early management decisions, particularly when stroke specialists are not immedi...
Application of Sparse Autoencoders to Enhance Mechanistic Interpretability of Large Language Models in Medicine [0.03%]
稀疏自编码器在医学领域增强大型语言模型机制可解释性中的应用
Andre Metzger,Shiv Patil,Lauren R Sugarmann et al.
Andre Metzger et al.
Large language models (LLMs) are being increasingly incorporated into clinical workflows due to their ability to synthesize medical knowledge and support diagnosis and treatment planning. However, their opaque internal decision-making proce...
Ethics and Fairness Considerations in AI-Based Deception Detection Technologies for Mental Health Applications: Focus Group Study [0.03%]
基于人工智能的精神健康应用中的谎言检测技术的伦理与公平性考量：焦点小组研究
Sayde Leya King,Serena Bhaskar,Julia Woodward et al.
Sayde Leya King et al.
Background: Artificial intelligence (AI) technologies are increasingly being integrated into mental health settings to support tasks such as clinical documentation and decision-making. In parallel, AI-enabled deception de...
Artificial Intelligence Remote Patient Monitoring for Predicting Overall Survival for Patients Undergoing Radical Cystectomy for Bladder Cancer: Exploratory Analysis of the Prospective Trial [0.03%]
用于预测膀胱癌根治性膀胱切除术患者总体生存率的远程智能患者监测：前瞻性试验的探索性分析
Yansong Liu,Pramit Khetrapal,Ronnie Strafford et al.
Yansong Liu et al.
Background: Previous studies have highlighted the benefits of using artificial intelligence-powered remote patient monitoring (AI RPM) in detecting health changes across various disease cohorts. However, the use of AI RPM...
Large Language Models in Clinical Trial Recruitment: Sociotechnical and Economic Framework Development Study [0.03%]
临床试验招募中大型语言模型的社会技术与经济框架开发研究
Qian Qian
Qian Qian
Background: Large language models (LLMs) have shown substantial promise in patient-trial matching, but most published studies still evaluate the performance under controlled technical conditions rather than within real re...
AI-Enabled Digital Health Promotion and Prevention: Computational Literature Review [0.03%]
基于人工智能的数字健康促进与预防：计算文献综述
Mariana Girão Carrilho,Diego Costa Pinto,Rafael Wagner et al.
Mariana Girão Carrilho et al.
Background: Health promotion aims to strengthen individuals' and communities' capacity to maintain health and well-being through behavior change, empowerment, and supportive environments. Achieving this requires intervent...
Review
JMIR AI. 2026 May 18:5:e84492. DOI:10.2196/84492 2026
Evaluating Medical Students' Perceptions of AI-Assisted Clinical Documentation (CarePilot): Cross-Sectional Study [0.03%]
医学生对AI辅助临床文档书写的感知评价（CarePilot）：横断面研究
Jonathan Bindi,Taylor Jamali,Talia Danze et al.
Jonathan Bindi et al.
Background: Artificial intelligence (AI) is increasingly being integrated into health care to streamline documentation and improve clinician efficiency. AI-powered documentation tools, such as CarePilot, may reduce admini...
Using Digital Phenotyping for Depression Screening in Community-Dwelling Older Adults: Bayesian Multilevel Hurdle Model Machine Learning Approach [0.03%]
基于贝叶斯多层障碍模型机器学习方法在社区老年人抑郁筛查中的数字表型应用
Moo-Kwon Chung,Hyo-Sang Lim,Sang Yup Lee et al.
Moo-Kwon Chung et al.
Background: With the rapidly aging population, mental health among older adults has received growing attention. Although the likelihood of experiencing depressive symptoms is higher in late adulthood, older adults are mor...
A Language Model for Pediatric Occupational Therapy Documentation: Model Development and Pilot Study [0.03%]
儿童作业疗法文件的语言模型：模型发展和初步研究
Rachel DiMaio,Tia Tuinstra,Trevor Yu et al.
Rachel DiMaio et al.
Background: In occupational therapy, progress notes and other client-related administrative tasks are essential for providing treatment but are time-consuming. Therapists spend at least as much time on these tasks as prov...
Natural Language Processing of Clinical Notes for Cancer Research and Patient Care Prior to Widespread Adoption of Generative AI: Scoping Review [0.03%]
临床笔记的自然语言处理在生成式人工智能广泛应用之前的癌症研究和患者护理：综述性评论
Alfred B Kayira,Hadeel R A Elyazori,Kevin Lybarger et al.
Alfred B Kayira et al.
Background: Clinical notes are the most abundant data type within electronic health records; however, their highly unstructured format presents significant challenges for supervised natural language processing (NLP) metho...
Review
JMIR AI. 2026 May 14:5:e73481. DOI:10.2196/73481 2026