Personalized vs. population-based speech models for multi-dimensional mental health prediction [0.03%]
个性化与面向人群的语音模型在多维度精神健康预测中的应用比较
Mashrura Tasnim,Jiayin He,Bo Cao et al.
Mashrura Tasnim et al.
Introduction: Mental disorders such as depression, anxiety, and stress are increasingly prevalent, particularly among young adults. Traditional assessment methods rely on self-reports and resource-intensive clinician inte...
Recognition and linking of discontinuous named entities in healthcare: a comparative performance analysis [0.03%]
医疗保健中的不连续实体识别与链接：性能比较分析
Areej Alhassan,Viktor Schlegel,Rina Carines Cabral et al.
Areej Alhassan et al.
Introduction: The recognition and linking of discontinuous named entities (DiscNEs) in healthcare remain challenging due to their fragmented structure and semantic complexity. This study presents a comparative analysis of...
Evaluating artificial intelligence large language models in dental education: a cross-sectional survey on usage, perceptions, and integration at a U.S. dental school [0.03%]
美国一所牙科学院中关于人工智能大型语言模型在牙科教育中的应用、感知和整合的横断面调查评估
Celine Sheng,Camie McFarland,Nikola Angelov et al.
Celine Sheng et al.
Introduction: The adoption of artificial intelligence (AI) in higher education presents opportunities and challenges for dental education. This study explores the use of Large Language Model (LLM) based AI tools, includin...
Rijul Gupta,Craig T Jin,Dhanshree R Gunjawate et al.
Rijul Gupta et al.
Objectives: This review aims to identify the key barriers to clinical application of Machine Learning (ML) in multi-class voice disorder classification. D...
Feasibility of weekly patient-reported symptom monitoring using patients' own smartphones in outpatient cancer chemotherapy: the SMART-PRO study [0.03%]
基于患者自身智能手机的门诊癌症化疗患者的周症状监测研究（SMART-PRO 研究）
Yutaka Sugawara,Momoko Kobayashi,Eri Mannoji et al.
Yutaka Sugawara et al.
Electronic patient-reported outcome (ePRO) systems using the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE) can improve symptom monitoring, but the feasibility of implementing such system...
Coralie S Phanord,Luka L Ruzic,Siddharth Kalyanasundaram et al.
Coralie S Phanord et al.
Background: Depression is highly heterogeneous and difficult to monitor or predict in daily life. One strategy for monitoring depressive symptoms is digital phenotyping, the real-time tracking of behaviors via personal de...
Reducing bias and enhancing equity in AI-enabled precision nutrition: addressing measurement error across wearables, multiomics, and dietary data [0.03%]
减少人工智能赋能的精准营养中的偏见和增强公平性：解决可穿戴设备、多组学和饮食数据中的测量误差问题
Andi Mai,Yuanyuan Luan,See Ling Loy et al.
Andi Mai et al.
Artificial intelligence (AI) can offer individualized dietary guidance based on multimodal data collected from various sources, including wearable sensors, high-dimensional multiomics and biomarker analyses, behavioral tracking, and self-re...
Determinants of technology adoption among healthcare professionals at Mogadishu hospitals using an extended UTAUT model [0.03%]
采用扩展的UTAUT模型分析摩加迪沙医院医护人员采纳技术行为的影响因素
Omar Osman Haji Abdi,Mohamed Jama Mohamed,Mohamed Ali Osman et al.
Omar Osman Haji Abdi et al.
The study used the expanded Unified Theory of Acceptance and usage of Technology (UTAUT) to identify the variables influencing the usage of technology by medical staff in hospitals in Mogadishu. This study aimed to identify the key factors ...
Editorial: Advances in generative artificial intelligence for mental health [0.03%]
组稿(Editorial): 用于精神健康的生成式人工智能的新进展
Nuo Han,Zengda Guan,Ang Li et al.
Nuo Han et al.
Digital marketing of e-cigarettes in Southeast Asia: a neglected digital health and platform governance challenge for youth protection [0.03%]
电子烟在东南亚的数字营销：一个被忽视的数字健康和平台治理挑战，关乎青少年保护
Myo Zin Oo,Soe Sandi Tint,Kong Sam An et al.
Myo Zin Oo et al.