Survey on Pain Detection Using Machine Learning Models: Narrative Review [0.03%]
使用机器学习模型进行疼痛检测的调查：叙事综述
Ruijie Fang,Elahe Hosseini,Ruoyu Zhang et al.
Ruijie Fang et al.
Background: Pain, a leading reason people seek medical care, has become a social issue. Automated pain assessment has seen notable advancements over recent decades, addressing a critical need in both clinical and everyday...
Review
JMIR AI. 2025 Feb 24:4:e53026. DOI:10.2196/53026 2025
Prompt Engineering an Informational Chatbot for Educating about Mental Health: Utilizing a Multi-Agent Approach for Enhanced Compliance with Prompt Instruction [0.03%]
利用多智能体方法提高对指令的遵守以教育心理健康的信息聊天机器人的提示工程
Per Niklas Waaler,Musarrat Hussain,Igor Molchanov et al.
Per Niklas Waaler et al.
Background: People with schizophrenia often present with cognitive impairments that may hinder their ability to learn about their condition. Education platforms powered by Large Language Models (LLMs) have the potential t...
Predicting Satisfaction With Chat-Counseling at a 24/7 Chat Hotline for the Youth: Natural Language Processing Study [0.03%]
针对青年的24/7在线聊天热线中对咨询聊天满意度的预测研究：自然语言处理研究
Silvan Hornstein,Ulrike Lueken,Richard Wundrack et al.
Silvan Hornstein et al.
Background: Chat-based counseling services are popular for the low-threshold provision of mental health support to youth. In addition, they are particularly suitable for the utilization of natural language processing (NLP...
Investigating the Classification of Living Kidney Donation Experiences on Reddit and Understanding the Sensitivity of ChatGPT to Prompt Engineering: Content Analysis [0.03%]
对Reddit上活体肾脏捐献经历的分类及ChatGPT对提示工程敏感度的理解：内容分析
Joshua Nielsen,Xiaoyu Chen,LaShara Davis et al.
Joshua Nielsen et al.
Background: Living kidney donation (LKD), where individuals donate one kidney while alive, plays a critical role in increasing the number of kidneys available for those experiencing kidney failure. Previous studies show t...
Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study [0.03%]
用于医疗保健分析和实施个人健康火车的隐私保护方法研究： federated deep learning研究报告
Ananya Choudhury,Leroy Volmer,Frank Martin et al.
Ananya Choudhury et al.
Background: The rapid advancement of deep learning in health care presents significant opportunities for automating complex medical tasks and improving clinical workflows. However, widespread adoption is impeded by data p...
Urgency Prediction for Medical Laboratory Tests Through Optimal Sparse Decision Tree: Case Study With Echocardiograms [0.03%]
基于最优稀疏决策树的医学检验紧急程度预测——以超声心动图为例研究
Yiqun Jiang,Qing Li,Yu-Li Huang et al.
Yiqun Jiang et al.
Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditi...
Identification of Use Cases, Target Groups, and Motivations Around Adopting Smart Speakers for Health Care and Social Care Settings: Scoping Review [0.03%]
识别用于健康和社会护理环境的智能扬声器用例、目标组和动机：综合审查
Sebastian Merkel,Sabrina Schorr
Sebastian Merkel
Background: Conversational agents (CAs) are finding increasing application in health and social care, not least due to their growing use in the home. Recent developments in artificial intelligence, machine learning, and n...
Review
JMIR AI. 2025 Jan 13:4:e55673. DOI:10.2196/55673 2025
Evaluating ChatGPT's Efficacy in Pediatric Pneumonia Detection From Chest X-Rays: Comparative Analysis of Specialized AI Models [0.03%]
评估ChatGPT在儿科肺炎胸部X光片检测中的有效性：专用AI模型的比较分析
Nitin Chetla,Mihir Tandon,Joseph Chang et al.
Nitin Chetla et al.
Enhancing Interpretable, Transparent, and Unobtrusive Detection of Acute Marijuana Intoxication in Natural Environments: Harnessing Smart Devices and Explainable AI to Empower Just-In-Time Adaptive Interventions: Longitudinal Observational Study [0.03%]
提高自然环境下的急性大麻中毒的可解释性、透明性和非侵入式检测：利用智能设备和可解释的人工智能赋能即时适应性干预：纵向观察性研究
Sang Won Bae,Tammy Chung,Tongze Zhang et al.
Sang Won Bae et al.
Background: Acute marijuana intoxication can impair motor skills and cognitive functions such as attention and information processing. However, traditional tests, like blood, urine, and saliva, fail to accurately detect a...
Geospatial Modeling of Deep Neural Visual Features for Predicting Obesity Prevalence in Missouri: Quantitative Study [0.03%]
基于深度神经视觉特征的地理空间建模在密苏里州预测肥胖流行率的定量研究
Butros M Dahu,Solaiman Khan,Imad Eddine Toubal et al.
Butros M Dahu et al.
Background: The global obesity epidemic demands innovative approaches to understand its complex environmental and social determinants. Spatial technologies, such as geographic information systems, remote sensing, and spat...