Digital health education in Australian universities: Trends, gaps, and future directions [0.03%]
澳大利亚高校数字健康教育现状、差距及未来方向
Tafheem Ahmad Wani,Michael Liem,James Boyd et al.
Tafheem Ahmad Wani et al.
Background: As healthcare systems increasingly embrace digital transformation, the need for a specialised digital health workforce, distinct from general clinical or IT roles, has become paramount. This study offers a nat...
Challenges and facilitators of electronic health record implementation: a scoping review [0.03%]
电子健康记录实施的挑战与促进因素：系统综述
Masume Dehghan,Anahita Behzadi,Mohammad Hossein Mehrolhassani et al.
Masume Dehghan et al.
Background and objective: The rapid advancement of technology has made eHealth a vital part of modern healthcare. Electronic Health Records (EHRs), as core tools of eHealth, enhance care quality, enable access to medical ...
The secrets of medical students' psychological resilience: a dual perspective of machine learning and path analysis [0.03%]
医学生的心理韧性有何秘诀——机器学习与路径分析双重视角
Wenyu Su,Huiyu Jia,Wenjing Chang et al.
Wenyu Su et al.
Background: As future healthcare workers, if medical students can enhance their psychological resilience, it will help them better cope with the pressures and challenges of their future work, thereby improving the overall...
Security practices and insider threats in Spanish healthcare centers: a survey-based risk assessment [0.03%]
西班牙医疗中心的安全实践和内部威胁：基于调查的风险评估
Isabel Herrera Montano,Susel Góngora Alonso,Soledad Sañudo García et al.
Isabel Herrera Montano et al.
Introduction: Insider threats pose a critical risk in healthcare environments, where Hospital Information Systems (HIS) manage sensitive patients data. Authorized users may intentionally or accidentally compromise data co...
Clinical effectiveness of a cloud-based dual-layer prescription review system: provincial integration across internet and outpatient care [0.03%]
基于云的双层处方审核系统的临床有效性：线上线下全省整合式医疗护理体系的构建及应用研究
Jinming Shi,Dongxu Sun,Jian Kang et al.
Jinming Shi et al.
Purpose: Ensuring medication safety remains a pressing challenge in fragmented healthcare systems, particularly with the rapid growth of Internet Hospitals and limited pharmacist resources. Existing prescription review to...
Scoping review on the economic aspects of machine learning applications in healthcare [0.03%]
关于机器学习在医疗保健方面经济影响的综述研究
Hanna von Gerich,Mikael Helenius,Iiris Hörhammer et al.
Hanna von Gerich et al.
Background: The development and use of artificial intelligence and machine learning technologies in healthcare have increased, prompting a need for evidence on their safety and value. Economic evaluations support healthca...
Refractive error detection in smartphone images via convolutional neural network [0.03%]
基于卷积神经网络的智能手机图像屈光不正检测方法
M K Michael Cheung,Zhongqi Yang,Xinwei Zhai et al.
M K Michael Cheung et al.
Background and objective: Refractive error, a common vision impairment, can cause serious problems such as amblyopia. Current vision screening relies on expensive equipment and trained optometrists, limiting accessibility...
Performance and improvement strategies for adapting generative large language models for electronic health record applications: A systematic review [0.03%]
适应生成型大型语言模型以用于电子健康记录应用的性能及改进策略：系统评价研究
Xinsong Du,Zhengyang Zhou,Yifei Wang et al.
Xinsong Du et al.
Purpose: To synthesize performance and improvement strategies for adapting generative LLMs in EHR analyses and applications. Methods: W...
Explainable machine learning models for early Alzheimer's disease detection using multimodal clinical data [0.03%]
基于多模态临床数据的早期阿尔茨海默病检测的可解释机器学习模型
Afeez Adekunle Soladoye,Nicholas Aderinto,Damilola Osho et al.
Afeez Adekunle Soladoye et al.
Background: Alzheimer's disease (AD) represents a significant global health challenge requiring early and accurate prediction for effective intervention. While machine learning models demonstrate promising capabilities in...
Diagnostic performance of newly developed large language models in critical illness cases: A comparative study [0.03%]
新型大型语言模型在危重病病例诊断性能的比较研究
Xintong Wu,Yu Huang,Qing He
Xintong Wu
Background: Large language models (LLMs) are increasingly used in clinical decision support, and newly developed models have demonstrated promising potential, yet their diagnostic performance for critically ill patients i...