Identifying factors that affect the use of health information technology in the treatment and management of hypertension [0.03%]
影响在高血压治疗和管理中使用健康信息科技的因素分析
Aysan Faezi,Hadi Lotfnezhad Afshar,Bahlol Rahimi
Aysan Faezi
Background: We conducted this study with the aim of identifying factors that affect the use of health information technology in the treatment and management of hypertension. ...
Individualized treatment decision model for inoperable elderly esophageal squamous cell carcinoma based on multi-modal data fusion [0.03%]
基于多模态数据融合的不可手术老年食管鳞癌个体化治疗决策模型
Yong Huang,Xiaoyu Huang,Anling Wang et al.
Yong Huang et al.
Background: This research aimed to develop a model for individualized treatment decision-making in inoperable elderly patients with esophageal squamous cell carcinoma (ESCC) using machine learning methods and multi-modal ...
Rachel B Seymour,Meghan K Wally,Joseph R Hsu;PRIMUM Group
Rachel B Seymour
Background: Prescription drug overdose and misuse has reached alarming numbers. A persistent problem in clinical care is lack of easy, immediate access to all relevant information at the actionable time. Prescribers must ...
Observational Study
BMC medical informatics and decision making. 2023 Oct 20;23(1):234. DOI:10.1186/s12911-023-02314-0 2023
Application and interpretation of machine learning models in predicting the risk of severe obstructive sleep apnea in adults [0.03%]
机器学习模型在预测成人重症阻塞性睡眠呼吸暂停风险中的应用与解释
Yewen Shi,Yitong Zhang,Zine Cao et al.
Yewen Shi et al.
Background: Obstructive sleep apnea (OSA) is a globally prevalent disease with a complex diagnostic method. Severe OSA is associated with multi-system dysfunction. We aimed to develop an interpretable machine learning (ML...
Using an adaptive network-based fuzzy inference system for prediction of successful aging: a comparison with common machine learning algorithms [0.03%]
采用自适应网络模糊推理系统预测成功老龄化：与常用机器学习算法的比较
Azita Yazdani,Mostafa Shanbehzadeh,Hadi Kazemi-Arpanahi
Azita Yazdani
Introduction: The global society is currently facing a rise in the elderly population. The concept of successful aging (SA) appeared in the gerontological literature to overcome the challenges and problems of population a...
Escape to the future - a qualitative study of physicians' views on the work environment, education, and support in a digital context [0.03%]
逃向未来——医生在数字化环境下的工作环境、教育和支持的定性研究
Maria Hägglund,Anna Kristensson Ekwall,Nadia Davoody et al.
Maria Hägglund et al.
Background: The use of remote services such as video consultations (VCs) has increased significantly in the wake of the COVID-19 pandemic. In Sweden, private healthcare providers offering VCs have grown substantially sinc...
Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals [0.03%]
基于深度学习和ECG信号时频表示的心律失常检测方法
Yared Daniel Daydulo,Bheema Lingaiah Thamineni,Ahmed Ali Dawud
Yared Daniel Daydulo
Background: Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically, ECG machines are utilized to diagnose and...
Correction: Development and validation of a case definition for problematic menopause in primary care electronic medical records [0.03%]
纠正：在初级保健电子病历中问题绝经病例定义的制定与验证
Anh N Q Pham,Michael Cummings,Nese Yuksel et al.
Anh N Q Pham et al.
Improving computerized decision support system interventions: a qualitative study combining the theoretical domains framework with the GUIDES Checklist [0.03%]
结合理论领域框架与GUIDES清单改进计算机决策支持系统干预措施的定性研究
Janet Yamada,Andrew Kouri,Sarah Nicole Simard et al.
Janet Yamada et al.
Background: Computerized clinical decision support systems (CDSSs) can improve care by bridging knowledge to practice gaps. However, the real-world uptake of such systems in health care settings has been suboptimal. We so...
Interpreting deep learning models for glioma survival classification using visualization and textual explanations [0.03%]
基于可视化和文本解释的深度学习模型的胶质瘤生存分类解读
Michael Osadebey,Qinghui Liu,Elies Fuster-Garcia et al.
Michael Osadebey et al.
Background: Saliency-based algorithms are able to explain the relationship between input image pixels and deep-learning model predictions. However, it may be difficult to assess the clinical value of the most important im...