Perceptions of Family Physicians About Applying AI in Primary Health Care: Case Study From a Premier Health Care Organization [0.03%]
家庭医生在初级卫生保健中应用AI的感知情况：来自一家著名医疗机构的案例研究
Muhammad Atif Waheed,Lu Liu
Muhammad Atif Waheed
Background: The COVID-19 pandemic has led to the rapid proliferation of artificial intelligence (AI), which was not previously anticipated; this is an unforeseen development. The use of AI in health care settings is incre...
Practical Considerations and Applied Examples of Cross-Validation for Model Development and Evaluation in Health Care: Tutorial [0.03%]
医疗保健中用于模型开发和评估的交叉验证的实际考虑和应用示例教程
Drew Wilimitis,Colin G Walsh
Drew Wilimitis
Cross-validation remains a popular means of developing and validating artificial intelligence for health care. Numerous subtypes of cross-validation exist. Although tutorials on this validation strategy have been published and some with app...
Application of Artificial Intelligence to the Monitoring of Medication Adherence for Tuberculosis Treatment in Africa: Algorithm Development and Validation [0.03%]
人工智能在非洲结核病治疗药物依从性监测中的应用：算法的开发与验证
Juliet Nabbuye Sekandi,Weili Shi,Ronghang Zhu et al.
Juliet Nabbuye Sekandi et al.
Background: Artificial intelligence (AI) applications based on advanced deep learning methods in image recognition tasks can increase efficiency in the monitoring of medication adherence through automation. AI has sparsel...
Artificial Intelligence in Health Care-Understanding Patient Information Needs and Designing Comprehensible Transparency: Qualitative Study [0.03%]
健康保健中的人工智能-理解患者信息需求和设计可以理解的透明度：质性研究
Renee Robinson,Cara Liday,Sarah Lee et al.
Renee Robinson et al.
Background: Artificial intelligence (AI) is as a branch of computer science that uses advanced computational methods such as machine learning (ML), to calculate and/or predict health outcomes and address patient and provi...
Self-Supervised Electroencephalogram Representation Learning for Automatic Sleep Staging: Model Development and Evaluation Study [0.03%]
面向自动睡眠分期的自监督脑电图表示学习模型研发与评价研究
Chaoqi Yang,Cao Xiao,M Brandon Westover et al.
Chaoqi Yang et al.
Background: Deep learning models have shown great success in automating tasks in sleep medicine by learning from carefully annotated electroencephalogram (EEG) data. However, effectively using a large amount of raw EEG da...
Artificial Intelligence-Enabled Software Prototype to Inform Opioid Pharmacovigilance From Electronic Health Records: Development and Usability Study [0.03%]
基于电子健康记录的AI软件原型促进阿片类药物药理警戒：开发及易用性研究
Alfred Sorbello,Syed Arefinul Haque,Rashedul Hasan et al.
Alfred Sorbello et al.
Background: The use of patient health and treatment information captured in structured and unstructured formats in computerized electronic health record (EHR) repositories could potentially augment the detection of safety...
Enabling Early Health Care Intervention by Detecting Depression in Users of Web-Based Forums using Language Models: Longitudinal Analysis and Evaluation [0.03%]
基于网络论坛的语言模型检测抑郁症以实现早期医疗干预：纵向分析与评估
David Owen,Dimosthenis Antypas,Athanasios Hassoulas et al.
David Owen et al.
Background: Major depressive disorder is a common mental disorder affecting 5% of adults worldwide. Early contact with health care services is critical for achieving accurate diagnosis and improving patient outcomes. Key ...
Application of a Comprehensive Evaluation Framework to COVID-19 Studies: Systematic Review of Translational Aspects of Artificial Intelligence in Health Care [0.03%]
综合性评价框架在COVID-19研究中的应用：医疗保健中人工智能的转化方面的系统回顾
Aaron Edward Casey,Saba Ansari,Bahareh Nakisa et al.
Aaron Edward Casey et al.
Background: Despite immense progress in artificial intelligence (AI) models, there has been limited deployment in health care environments. The gap between potential and actual AI applications is likely due to the lack of...
Review
JMIR AI. 2023 Jul 6:2:e42313. DOI:10.2196/42313 2023