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...
Leveraging Large Language Models to Improve the Readability of German Online Medical Texts: Evaluation Study [0.03%]
利用大型语言模型改善德语在线医学文本可读性的研究：评估研究
Amela Miftaroski,Richard Zowalla,Martin Wiesner et al.
Amela Miftaroski et al.
Background: Patient education materials (PEMs) found online are often written at a complexity level too high for the average reader, which can hinder understanding and informed decision-making. Large language models (LLMs...
Assessment of the Modified Rankin Scale in Electronic Health Records with a Fine-tuned Large Language Model [0.03%]
基于精细调整的大规模语言模型评估电子健康记录中的改良Rankin量表
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 ...
Treatment Recommendations for Clinical Deterioration on the Wards: Development and Validation of Machine Learning Models [0.03%]
住院患者病情恶化处理建议：机器学习模型的开发与验证
Eric Pulick,Kyle A Carey,Tonela Qyli et al.
Eric Pulick et al.
Background: Clinical deterioration in general ward patients is associated with increased morbidity and mortality. Early and appropriate treatments can improve outcomes for such patients. While machine learning (ML) tools ...
The Role of AI in Improving Digital Wellness Among Older Adults: Comparative Bibliometric Analysis [0.03%]
人工智能在改善老年人数字福祉中的作用：文献计量分析比较研究
Naveh Eskinazi,Moti Zwilling,Adilson Marques et al.
Naveh Eskinazi et al.
Background: Advances in artificial intelligence (AI) have revolutionized digital wellness by providing innovative solutions for health, social connectivity, and overall well-being. Despite these advancements, the older po...
Explainable Multitask Burnout Prediction Using Adaptive Deep Learning (EMBRACE) for Resident Physicians: Algorithm Development and Validation Study [0.03%]
基于自适应深度学习的住院医师倦怠预测解释性多任务算法研究（拥抱算法）
Saima Alam,Mohammad Arif Ul Alam
Saima Alam
Background: Medical residency is characterized by high stress, long working hours, and demanding schedules, leading to widespread burnout among resident physicians. Although wearable sensors and machine learning (ML) mode...
Assessing the Quality of AI Responses to Patient Concerns About Axial Spondyloarthritis: Delphi-Based Evaluation [0.03%]
基于德尔菲法的评估：人工智能对轴向强直性脊柱炎患者关切的回答质量评估
Jiaxin Bai,Xiaojian Ji,Jiali Yu et al.
Jiaxin Bai et al.
Background: Axial spondyloarthritis (axSpA) is a chronic autoinflammatory disease with heterogeneous clinical features, presenting considerable complexity for sustained patient self-management. Although the use of large l...
Performance of a Small Language Model Versus a Large Language Model in Answering Glaucoma Frequently Asked Patient Questions: Development and Usability Study [0.03%]
小型语言模型与大型语言模型在回答青光眼常见患者问题的表现比较：发展和可用性研究
Adriano Cypriano Faneli,Rafael Scherer,Rohit Muralidhar et al.
Adriano Cypriano Faneli et al.
Background: Large language models (LLMs) have been shown to answer patient questions in ophthalmology similar to human experts. However, concerns remain regarding their use, particularly related to patient privacy and pot...