Evaluating the efficacy of digital otoscopes in rural pediatric otitis media diagnosis: A comparative study of general practitioners and ENT specialists [0.03%]
数字耳镜在农村儿童急性中耳炎诊断中的有效性评估：全科医生与耳鼻喉专科医生的对比研究
Najmeh Pourshahrokhi,Somaye Norouzi,Aliasghar Arabi Mianroodi et al.
Najmeh Pourshahrokhi et al.
Background: Otitis media is a prevalent childhood illness, particularly among specific groups. However, its diagnosis has been of a serious issue, which is exacerbated in underprivileged regions with limited access to Ear...
Process evaluation of the implementation of a personalized digital care pathway tool using the RE-AIM framework [0.03%]
基于RE-AIM框架的个性化数字护理路径工具实施过程评价
F A C J Heijsters,E C Cornelissen,M C de Bruijne et al.
F A C J Heijsters et al.
Objective: This study evaluated the implementation of a Personalized Digital Care Pathway (PDCP) tool in the context of three different patient groups (i.e. scar clinic, cleft care and gender-affirming care). We assessed ...
Digital divide and health professional shortages: telehealth access for chronic disease management in rural Florida [0.03%]
数字鸿沟与卫生专业人员短缺对佛罗里达州农村地区慢性病管理的远程医疗利用的影响研究
Di Shang,Cynthia Williams,Aishwarya Joshi et al.
Di Shang et al.
Background: This study examines telehealth utilization among Medicare and Medicaid beneficiaries with chronic diseases in geographically vulnerable areas of Florida during COVID-19. ...
What digital competencies should medical students in China possess in the AI era? [0.03%]
人工智能时代中国的医学生应具备哪些数字能力？
Jinjuan Chen,Xiaorong Hou,Yalan Lv et al.
Jinjuan Chen et al.
Objective: With the advancement of the digital society and the extensive application of digital medical technologies, the demand for digital competencies among medical students is becoming increasingly critical. Digital c...
Toward responsible AI governance: Balancing multi-stakeholder perspectives on AI in healthcare [0.03%]
负责任的AI治理：医疗保健领域中平衡多方利益相关者的AI观点
Leon Rozenblit,Amy Price,Anthony Solomonides et al.
Leon Rozenblit et al.
Introduction: The rapid integration of artificial intelligence (AI) into healthcare presents significant governance challenges, requiring balanced approaches that safeguard safety, efficacy, equity, and trust (SEET). This...
Corrigendum to "Identifying potential medical aid beneficiaries using machine learning: A Korean Nationwide cohort study" [Int. J. Med. Inform. 195 (2025) 105775] [0.03%]
关于“使用机器学习识别潜在的医疗援助受益者：一项韩国全国队列研究”的勘误声明
Junmo Kim,Su Hyun Park,Hyesu Lee et al.
Junmo Kim et al.
Insights from high and low clinical users of telemedicine: a mixed-methods study of clinician workflows, sentiments, and user experiences [0.03%]
远程医疗高使用率和低使用率临床医生的见解——一种混合研究方法：探索临床医生的工作流程、观点及用户体验
Jennifer Sumner,Ravi Shankar,Anjali Bundele et al.
Jennifer Sumner et al.
Background: Teleconsultation is a valuable tool in healthcare, but systematic evaluation of workflow processes (comparing teleconsultation to in-person visits) and the nuanced experiences of high and low clinical users of...
AI in primary care: Comparing ChatGPT and family physicians on patient queries [0.03%]
初级保健中的AI：比较ChatGPT和家庭医生对患者问题的答复能力
Muhammed İnan,Özlem Suvak,Cenk Aypak
Muhammed İnan
Objective: The integration of artificial intelligence (AI) in medicine has led to growing interest in its applications for primary care. This study evaluates and compares the responses of ChatGPT-4o and family physicians ...
Staff expectations for the implementation of digital remote monitoring in services for people with psychosis: A qualitative study using normalisation process theory [0.03%]
运用正常化过程理论进行的定性研究：精神病患者的照护人员实施数字远程监控的期待
Hannah Ball,Emily Eisner,Jennifer Nicholas et al.
Hannah Ball et al.
Background: Digital remote monitoring (DRM) utilises devices such as smartphones and wearables to remotely collect health-related data, providing insights into the mental health of individuals with psychosis. This data ca...
Machine learning techniques for stroke prediction: A systematic review of algorithms, datasets, and regional gaps [0.03%]
基于机器学习的卒中预测研究：算法、数据集及地域差异系统综述
Afeez Adekunle Soladoye,Nicholas Aderinto,Mayowa Racheal Popoola et al.
Afeez Adekunle Soladoye et al.
Background: Stroke is a leading cause of mortality and disability worldwide, with approximately 15 million people suffering strokes annually. Machine learning (ML) techniques have emerged as powerful tools for stroke pred...