Artificial intelligence-enhanced electrocardiogram for the detection of rheumatic heart disease [0.03%]
人工智能增强心电图在风湿性心脏病检测中的应用
Raeesa Bhorat,David M Harmon,Kan Liu et al.
Raeesa Bhorat et al.
Aims: Rheumatic heart disease (RHD) remains the most prevalent acquired cardiovascular disease among young adults in developing countries, and there is a critical need for an efficient, affordable, and available screening...
Development and validation of clinical prediction models for personalized renal function monitoring in people with heart failure in primary care: the RENAL-HF study protocol [0.03%]
初级保健中个性化心力衰竭患者肾功能监测的临床预测模型的开发和验证：RENAL-HF研究方案
Alexandar Vincent-Paulraj,Matthew J Carr,David A Jenkins et al.
Alexandar Vincent-Paulraj et al.
Aims: Heart failure (HF) is a growing problem in society with an ageing population and many patients with heart failure are affected by renal dysfunction. The RENAL-HF project aims to develop predictive risk models to sup...
Prediction of vasovagal syncope using artificial intelligence-enabled smartwatch photoplethysmography-derived heart rate variability [0.03%]
基于人工智能的智能手表光电容积描记心率变异性在血管迷走性晕厥预测中的应用
Hak Seung Lee,Junho Song,Moonki Jung et al.
Hak Seung Lee et al.
Aims: Vasovagal syncope (VVS) can cause injury and impaired quality of life, and effective prevention requires timely warning before loss of consciousness. To evaluate whether smartwatch photoplethysmography (PPG)-derived...
Wearable-Echo-FM: an ECG echo foundation model for 1-lead electrocardiography [0.03%]
可穿戴回声FM：一种单导联心电图的ECG回声基础模型
Elizabeth Knight,Evangelos K Oikonomou,Arya Aminorroaya et al.
Elizabeth Knight et al.
Aims: Artificial intelligence (AI) models can now detect patterns of structural heart diseases (SHDs) from electrocardiograms (ECGs), though scaling them requires the broader use of 1-lead ECGs that are now ubiquitous in ...
Study design of the InTakeCare trial: a digital health solution to monitor and improve medication adherence in hypertensive patients [0.03%]
InTakeCare试验研究设计：一种数字健康解决方案，用于监测和改善高血压患者的药物依从性
Emanuele Tauro,Alessandra Gorini,Martina Vigorè et al.
Emanuele Tauro et al.
Aims: The InTakeCare Trial aims to develop, implement, and clinically validate a novel digital health solution (DHS) to improve medication adherence (MA) in patients with arterial hypertension. This initiative responds to...
Artificial intelligence adoption in French cardiovascular care: a multiprofessional survey of barriers and facilitators [0.03%]
法国心血管护理中人工智能应用的障碍与促进因素多职业调查研究
Nabil Bouali,Séverine Domart,Walid Amara et al.
Nabil Bouali et al.
Aims: Responsible adoption of artificial intelligence (AI) in cardiology remains uneven. We aimed to map knowledge, attitudes, beliefs and practices among cardiovascular professionals in France and to identify levers for ...
Tolga Hayit,Ibrahim Karabayir,David Herrington et al.
Tolga Hayit et al.
The electrocardiographic sex index (ESI) was developed in adults to capture continuous electrocardiogram (ECG) features associated with biological sex, but its behaviour in children, whose ECG morphology changes substantially through growth...
AI-driven voltage map analysis for optimizing catheter ablation strategy in atrial fibrillation: a proof-of-concept study [0.03%]
基于人工智能的电压图分析以优化房颤导管消融策略的概念验证研究
Takeshi Tohyama,Kazuo Sakamoto,Tomomi Nagayama et al.
Takeshi Tohyama et al.
Aims: Pulmonary vein isolation (PVI) has been established as the standard catheter ablation (CA) strategy for atrial fibrillation (AF). However, approximately 20-40% of patients experience recurrence after CA. Although th...
Artificial intelligence-enhanced wearable technology enables ventricular arrhythmia prediction [0.03%]
人工智能增强的可穿戴技术能够预测室性心律失常
Maarten Z H Kolk,Diana My Frodi,Joss Langford et al.
Maarten Z H Kolk et al.
Aims: Patterns in physical behaviour may be associated with an increased risk of ventricular arrhythmia. We examined associations between temporal dynamics in physical behaviour measured through wearable technology and th...
Open science requires trust and rigour: a framework for responsible evaluation of shared AI-ECG tools [0.03%]
开放科学需要信任和严谨性：负责任地评估共享AI心电图工具有框架
Lovedeep S Dhingra,Philip M Croon,Evangelos K Oikonomou et al.
Lovedeep S Dhingra et al.