Explainable Logistic Regression for Heart Disease Risk Prediction in Community and Clinical Populations: Development and External Validation Study [0.03%]
面向社区和临床人群的心脏病风险预测的可解释逻辑回归方法：研发与外部验证研究
Peihua Tong,Hui Hu,Ling Tong
Peihua Tong
Background: Heart disease is a leading cause of morbidity and mortality worldwide. Although machine learning models can achieve strong predictive performance, their limited interpretability hampers clinical adoption. Logi...
Using Patient-Held Devices to Measure Variations in Resting Heart Rate and Step Count Prior to Presentation With an Acute Illness: International, Multicenter Flash Mob Feasibility Study [0.03%]
使用患者持有的设备在出现急性疾病之前测量静息心率和步数的差异：国际多中心快闪可行性研究
Jason G A den Duijn,Ahmed A M Hajjaj,John Kellett et al.
Jason G A den Duijn et al.
Background: Many patients experience a gradual decline in health before seeking hospital care, with subtle changes in vital signs such as increased heart rate or decreased mobility. Recognizing deviations from baseline vi...
Observational Study
JMIR cardio. 2025 Dec 15:9:e76218. DOI:10.2196/76218 2025
Outcomes of Team-Based Digital Monitoring of Patients With Multiple Chronic Conditions: Semiparametric Event Study [0.03%]
基于团队的数字监测在多发慢性病患者中的结局：半参数事件研究
Ross Graham,Itzik Fadlon,Parag Agnihotri et al.
Ross Graham et al.
Background: Remote patient monitoring (RPM) has emerged as an effective strategy for controlling hypertension by enabling patients to collect and transmit blood pressure (BP) data outside the clinic and supporting proacti...
Telecardiology Activities in Hospital and University Cardiology Facilities in Italy: Survey Study [0.03%]
意大利医院和大学心脏病机构的心电卡iology活动调查研究
Manuela Bocchino,Elvira Agazio,Cecilia Damiano et al.
Manuela Bocchino et al.
Background: Telemedicine enables the provision of health services at a distance using information and communication technologies and includes different types of services: telemonitoring, remote control, virtual visit or t...
The Impact of Digital Intervention Messages Targeting Users With High Blood Pressure Events: Retrospective Real-World Study [0.03%]
针对高血压患者的数字干预信息的影响：回顾性现实世界研究
Yifat Fundoiano-Hershcovitz,Inbar Breuer Asher,Marilyn D Ritholz et al.
Yifat Fundoiano-Hershcovitz et al.
Background: Effective hypertension management, particularly through self-care strategies, remains a significant public health challenge. Despite widespread awareness, only approximately 1 in 5 adults achieves adequate blo...
Physicians' Use of Electronic Health Record Data Elements and Decision Support Tools in Heart Failure Management: User-Centered Cross-Sectional Survey Study [0.03%]
心力衰竭管理中医师利用电子健康记录数据和决策支持工具的使用情况：以用户为中心的横断面调查研究
Mohamed S Ali,Bruna Oewel,Kaitlyn M Greer et al.
Mohamed S Ali et al.
Background: The management of heart failure (HF) requires complex, data-driven decision-making. Although electronic health record (EHR) systems and clinical decision support (CDS) tools can streamline access to essential ...
Web-Based Platform for the Chilean Cardiac Surgery Registry: Algorithm Development and Validation Study [0.03%]
基于网络的智利心脏外科注册平台研发与验证研究
Sergio Guinez-Molinos,Enrique Seguel,Jaime Gonzalez et al.
Sergio Guinez-Molinos et al.
Background: Cardiac surgeries in Chile lack a national registry for systematic data collection and analysis, limiting insights into procedural outcomes and patient demographics. In response to this gap, we developed a web...
Photoplethysmography-Based Machine Learning Approaches for Atrial Fibrillation Burden: Algorithm Development and Validation [0.03%]
基于光容积描记术的心房颤动负担的机器学习方法：算法开发与验证
Hong Wang,Binbin Liu,Hui Zhang et al.
Hong Wang et al.
Background: Atrial fibrillation (AF) burden is associated with cardiovascular events such as stroke and heart failure. Recent advancements in photoplethysmography (PPG) technology have provided new insights into noninvasi...
Patient Preferences for Using Remote Care Technology in Heart Failure: Discrete Choice Experiment [0.03%]
心力衰竭患者使用远程护理技术的倾向性研究：离散选择实验
Ahmed Al-Naher,Jennifer Downing,Dyfrig Hughes et al.
Ahmed Al-Naher et al.
Background: Remote care technology has been used to bridge the gap between health care in a clinical setting and in the community, all the more essential post-COVID. Patients with chronic conditions may benefit from inter...
Serial 12-Lead Electrocardiogram-Based Deep-Learning Model for Hospital Admission Prediction in Emergency Department Cardiac Presentations: Retrospective Cohort Study [0.03%]
基于急诊科心脏病例的住院预测的序列12导联心电图深度学习模型：回顾性队列研究
Arda Altintepe,Kutsev Bengisu Ozyoruk
Arda Altintepe
Background: Emergency department (ED) crowding is often attributed to a slow hospitalization process, leading to reduced quality of care. Predicting early disposition in patients presenting with cardiac issues is challeng...