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
Evaluating AI-Mediated Health Communication via Large Language Model-Based Frequently Asked Questions Rewriting to Foster Clinical Trial Participation: Comparative Survey Study [0.03%]
基于大型语言模型的FAQ重写以促进临床试验参与的AI中介健康交流评估：比较调查研究
Ching-Hua Chuan,Jiajing Tang,Zixiao Yang et al.
Ching-Hua Chuan et al.
Background: Effective communication about clinical trials is essential, as low enrollment undermines scientific validity and contributes to health care inequities. However, recruitment remains a persistent challenge, part...
Methodological Approaches to and Reported Performance of Applications of Automated Machine Learning in Diabetes Risk Prediction: Rapid Review [0.03%]
糖尿病风险预测中自动机器学习应用的方法学方法及性能表现：快速回顾
Alexandre Castonguay,Sandrine Hegg-Deloye,Arthur Chatton et al.
Alexandre Castonguay et al.
Background: Type 2 diabetes (T2D) is a complex, chronic condition that imposes a substantial burden on health care systems. Prevention and early detection are critical to mitigating its impact. Automated machine learning ...
Review
JMIR AI. 2026 May 12:5:e87819. DOI:10.2196/87819 2026
Public Expectations for Food and Drug Administration Approval of AI-Based Clinical Decision Support Tools: Quantitative Study [0.03%]
公众期望美国食品和药物管理局批准基于人工智能的临床决策支持工具：定量研究
Gloria Maria Carmona Clavijo,Paige Nong,Sean Tan et al.
Gloria Maria Carmona Clavijo et al.
Background: Regulation of artificial intelligence (AI) has been slow relative to the pace of its integration into health care. Several AI diagnostic tools for diabetic retinopathy (DR) have already received Food and Drug ...
Unlocking the Full Potential of Health Care Teams: How Artificial Intelligence Can Help [0.03%]
释放医疗团队全部潜力：人工智能如何助力
Manchi Monica Hsu,Benny Bikash Pokharel,Jacqueline Kueper et al.
Manchi Monica Hsu et al.
Developing effective health care teams is critical to meet the rising complexity in patient care. However, optimizing team composition, interpersonal dynamics, and care processes in complex health care systems requires processing vast amoun...