Mental health app crisis support assessment framework: development and pilot testing [0.03%]
心理健康应用危机支持评估框架：研发及试点测试研究
Anastasiia Knysh,Taras Pohrebniak
Anastasiia Knysh
Mental health applications increasingly serve as stand-alone interventions or adjuncts to clinical care, yet their capacity to support users experiencing acute psychological distress remains poorly characterized. This study introduces the M...
Crisis support teams' technological openness and learning attitudes toward the AI based virtual patient system crisis support VR [0.03%]
危机支持团队的技术开放性和学习态度面向基于人工智能的虚拟患者系统危机支持VR
Sophie Kjerstin Mårtensson,Charlotte Hveem,Maurice Lamb et al.
Sophie Kjerstin Mårtensson et al.
Background: Against the backdrop of escalating global humanitarian crises, innovative didactic simulations are becoming increasingly important. A promising alternative to traditional classroom-based didactics for learning...
SENTINEL-Chain: a blockchain-integrated privacy-preserving framework for secure healthcare data publishing [0.03%]
哨兵链：一种用于安全发布医疗数据的区块链集成隐私保护框架
Nagaraj Segar,Vijayarajan Vijayan
Nagaraj Segar
Introduction: Electronic health records (EHRs) are central to healthcare analytics, but their granularity increases re-identification risk when shared. Conventional privacy-preserving methods including k-anonymity, l-dive...
Digital health tools and point solutions-pitfalls in population health program measurement [0.03%]
数字化健康工具和点解决方案-人口健康管理计划评估中的陷阱
Carolyn Langer,James Shaw,Wiljeana Glover
Carolyn Langer
Digital health tools are generally poorly regulated and often lack strong research evidence, posing challenges for purchasers of point solutions such as employer groups and insurers. Point solutions, which are digital tools designed to mana...
Performance of large language models in delivering accurate and comprehensible patient information on heart failure and cardiomyopathy [0.03%]
大型语言模型在提供心力衰竭和心肌病患者信息的准确性和可读性方面的表现
Christoph Reich,Jule Leverenz,Charlotte Brand et al.
Christoph Reich et al.
Background: Large language models (LLMs) are increasingly used by patients seeking cardiovascular health information through digital platforms. However, their accuracy and suitability for providing guidance on heterogeneo...
Brenda Adhiambo Odero,Candice Groenewald
Brenda Adhiambo Odero
This mini review examines the emerging use of digital platforms for ethics review (DPER) and the extent to which research ethics committees (RECs) are prepared for digital transformation and operational autonomy. Drawing on a structured ana...
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...