Ambient AI Documentation and Patient Satisfaction in Outpatient Care: Retrospective Pilot Study [0.03%]
门诊护理中的环境人工智能文档与患者满意度：回顾性试点研究
Eric Davis,Sarah Davis,Kristina Haralambides et al.
Eric Davis et al.
Background: Patient experience is a critical consideration for any health care institution. Leveraging artificial intelligence (AI) to improve health care delivery has rapidly become an institutional priority across the U...
Clinical Evidence Linkage From the American Society of Clinical Oncology 2024 Conference Poster Images Using Generative AI: Exploratory Observational Study [0.03%]
使用生成式人工智能从美国临床肿瘤学会2024年大会的海报图像中链接临床证据：探索性观察研究
Carlos Areia,Michael Taylor
Carlos Areia
Background: Early-stage clinical findings often appear only as conference posters circulated on social media. Because posters rarely carry structured metadata, their citations are invisible to bibliometric and alternative...
Ethical Risks and Structural Implications of AI-Mediated Medical Interpreting [0.03%]
基于人工智能的医疗口译伦理风险及结构性影响
Alexandra Lopez Vera
Alexandra Lopez Vera
Artificial intelligence (AI) is increasingly used to support medical interpreting and public health communication, yet current systems introduce serious risks to accuracy, confidentiality, and equity, particularly for speakers of low-resour...
Exploring Clinician Perspectives on Artificial Intelligence in Primary Care: Qualitative Systematic Review and Meta-Synthesis [0.03%]
探索人工智能在初级保健中临床医生的观点：定性系统评价和综合分析
Robin Bogdanffy,Alisa Mundzic,Peter Nymberg et al.
Robin Bogdanffy et al.
Background: Recent advances have highlighted the potential of artificial intelligence (AI) systems to assist clinicians with administrative and clinical tasks, but concerns regarding biases, lack of regulation, and potent...
Review
JMIR AI. 2026 Feb 5:5:e72210. DOI:10.2196/72210 2026
Human-Generative AI Interactions and Their Effects on Beliefs About Health Issues: Content Analysis and Experiment [0.03%]
人与生成式人工智能互动及其对健康问题信念的影响：内容分析和实验研究
Linqi Lu,Yanshu Sybil Wang,Jiawei Liu et al.
Linqi Lu et al.
Augmenting LLM with Prompt Engineering and Supervised Fine-Tuning in NSCLC TNM Staging: Framework Development and Validation [0.03%]
基于提示工程和有监督微调的LLM在非小细胞肺癌TNM分期中的应用：框架研发与验证
Ruonan Jin,Chao Ling,Yixuan Hou et al.
Ruonan Jin et al.
Background: Accurate TNM staging is fundamental for treatment planning and prognosis in non-small cell lung cancer (NSCLC). However, its complexity poses significant challenges, particularly in standardizing interpretatio...
Titus Tunduny,Bernard Shibwabo
Titus Tunduny
Background: Artificial intelligence (AI) has, in the recent past, experienced a rebirth with the growth of generative AI systems such as ChatGPT and Bard. These systems are trained with billions of parameters and have ena...
Review
JMIR AI. 2026 Feb 3:5:e69985. DOI:10.2196/69985 2026
Message Humanness as a Predictor of AI's Perception as Human: Secondary Data Analysis of the HeartBot Study [0.03%]
消息人性作为预测AI被感知为人的一种方法：对HeartBot研究的二次数据分析
Haruno Suzuki,Jingwen Zhang,Diane Dagyong Kim et al.
Haruno Suzuki et al.
Background: Artificial intelligence (AI) chatbots have become prominent tools in health care to enhance health knowledge and promote healthy behaviors across diverse populations. However, factors influencing the perceptio...
Large Language Model-based Chatbots and Agentic AI for Mental Health Counseling: A Systematic Review of Methodologies, Evaluation Frameworks, and Ethical Safeguards [0.03%]
基于大型语言模型的聊天机器人和代理智能在心理健康咨询中的应用：方法、评价框架及伦理保障的系统性综述
Ha Na Cho,Kai Zheng,Jiayuan Wang et al.
Ha Na Cho et al.
Background: Large language model (LLM)-based chatbots have rapidly emerged as tools for digital mental health (MH) counseling. However, evidence on their methodological quality, evaluation rigor, and ethical safeguards re...
Evaluating an AI Decision Support System for the Emergency Department: Retrospective Study [0.03%]
一项回顾性研究：评估急诊科人工智能决策支持系统的效果
Yvette Van Der Haas,Wiesje Roskamp,Lidwina Elisabeth Maria Chang-Willems et al.
Yvette Van Der Haas et al.
Background: Overcrowding in the emergency department (ED) is a growing challenge, associated with increased medical errors, longer patient stays, higher morbidity, and increased mortality rates. Artificial intelligence (A...