A Pragmatic Framework for Federated Learning Risk and Governance in Academic Medical Centers [0.03%]
学术医学中心联合学习的实用风险与治理框架
Daniel Bottomly,Bridget Barnes,Kuli Mavuwa et al.
Daniel Bottomly et al.
With the rapid development of artificial intelligence (AI), particularly large language models, there is growing interest in adopting AI approaches within academic medical centers (AMCs). However, the vast amounts of data required for AI an...
AI-Enabled Personalization of Semaglutide Therapy in Type 2 Diabetes: Systematic Review With an Integration Framework [0.03%]
基于人工智能的利拉鲁肽治疗2型糖尿病个性化策略的系统评价及整合框架
Ghinwa Barakat,Samer El Hajj Hassan,Hanane Akhdar et al.
Ghinwa Barakat et al.
Background: Type 2 diabetes mellitus (T2D) is a rapidly growing global health concern requiring innovative treatment methods. Ozempic (semaglutide), a glucagon-like peptide-1 receptor agonist, has proven consistent effect...
Review
JMIR AI. 2026 Mar 9:5:e86960. DOI:10.2196/86960 2026
Facial Expression-Based Evaluation of the Emotion Estimation Software Kokoro Sensor in Healthy Individuals: Validation and Reliability Pilot Study [0.03%]
基于面部表情的健康人Kokoro情绪估计软件有效性评价：有效性和可靠性验证试点研究
Shota Yoshihara,Satoru Amano,Kayoko Takahashi
Shota Yoshihara
Background: In recent years, artificial intelligence (AI) systems have increasingly been used to assess emotional states in health care. AI offers a safe, quick, user-friendly, and objective emotional evaluation method. H...
Assessment of the Modified Rankin Scale in Electronic Health Records With a Fine-Tuned Large Language Model: Development and Internal Validation [0.03%]
基于精调的大语义模型的改良Rankin量表电子健康记录评估：开发与内部验证
Luis Silva,Marcus Milani,Sohum Bindra et al.
Luis Silva et al.
Background: The modified Rankin scale (mRS) is an important metric in stroke research, often used as a primary outcome in clinical trials and observational studies. The mRS can be assessed retrospectively from electronic ...
Explaining the Slow Adoption of AI Innovations in Health Care: Network Analysis Approach [0.03%]
基于网络分析的医疗保健领域人工智能创新应用缓慢的原因探究
Petra Apell,Sara Locher,Annie Milde et al.
Petra Apell et al.
Background: Artificial intelligence (AI) is a topic of considerable hype, with many actors sensing its high potential for health care applications. Despite this, the adoption has been slow, with few applications being imp...
Performance of Large Language Models Under Input Variability in Health Care Applications: Dataset Development and Experimental Evaluation [0.03%]
医疗应用中大型语言模型在输入变化下的表现：数据集开发与实验评估
Saubhagya Joshi,Monjil Mehta,Sarjak Maniar et al.
Saubhagya Joshi et al.
Background: Large language models (LLMs) are increasingly integrated into health care, where they contribute to patient care, administrative efficiency, and clinical decision-making. Despite their growing role, the abilit...
AI-Generated Images of Substance Use and Recovery: Mixed Methods Case Study [0.03%]
人工智能生成的物质使用和康复图像：混合方法案例研究
Kathryn Heley,Jeffrey K Hom,Linnea Laestadius
Kathryn Heley
Background: Images created with generative artificial intelligence (AI) tools are increasingly used for health communication due to their ease of use, speed, accessibility, and low cost. However, AI-generated images may b...
Application of AI Models for Preventing Surgical Complications: Scoping Review of Clinical Readiness and Barriers to Implementation [0.03%]
人工智能模型预防手术并发症的应用：临床应用准备情况及实施障碍的研究综述
Kjersti Mevik,Ashenafi Zebene Woldaregay,Eva Lindell Jonsson et al.
Kjersti Mevik et al.
Background: The impact of surgical complications is substantial and multifaceted, affecting patients and their families, surgeons, and health care systems. Despite the remarkable progress in artificial intelligence (AI), ...
Review
JMIR AI. 2026 Feb 17:5:e75064. DOI:10.2196/75064 2026
Evaluation of Large Language Models for Peer Review in Transplantation Research: Algorithm Validation Study [0.03%]
移植研究同行评审中大型语言模型的评估：算法验证研究
Selena Ming Shen,Zifu Wang,Krittika Paul et al.
Selena Ming Shen et al.
Background: Peer review remains central to ensuring research quality, yet it is constrained by reviewer fatigue and human bias. The rapid rise in scientific publishing has worsened these challenges, prompting interest in ...
Large Language Models for Health Care Text Classification: Systematic Review [0.03%]
用于医疗保健文本分类的大语言模型：系统评价
Hajar Sakai,Sarah S Lam
Hajar Sakai
Background: Large language models (LLMs) have fundamentally transformed approaches to natural language processing tasks across diverse domains. In health care, accurate and cost-efficient text classification is crucial-wh...
Review
JMIR AI. 2026 Feb 11:5:e79202. DOI:10.2196/79202 2026