Rajesh Kabra,Sharat Israni,Bharat Vijay et al.
Rajesh Kabra et al.
Artificial intelligence (AI) and machine learning (ML) have significantly impacted the field of cardiovascular medicine, especially cardiac electrophysiology (EP), on multiple fronts. The goal of this review is to familiarize readers with t...
Exploring telerobotic cardiac catheter ablation in a rural community hospital: A pilot study [0.03%]
在农村社区医院探索远程机器人心脏导管消融：初步研究
Brian Serafini,Lanu Kim,Basil M Saour et al.
Brian Serafini et al.
Background: Telerobotic surgery could improve access to specialty procedures such as cardiac catheter ablation in rural and underserved regions in the United States and worldwide. Advancements in telecommunications, inter...
Tandem deep learning and logistic regression models to optimize hypertrophic cardiomyopathy detection in routine clinical practice [0.03%]
串联深度学习和逻辑回归模型以优化肥厚型心肌病在常规临床实践中的检测
Maren Maanja,Peter A Noseworthy,Jeffrey B Geske et al.
Maren Maanja et al.
Background: An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM). However, its application in routine clinical practice may be c...
Inside the "black box": Embedding clinical knowledge in data-driven machine learning for heart disease diagnosis [0.03%]
黑盒子内部：在数据驱动的机器学习中嵌入临床知识用于心脏病诊断
James Meng,Ruiming Xing
James Meng
Background: Ischemic heart disease (IHD) caused by the narrowing of coronary arteries is a major cause of morbidity and mortality worldwide. Clinical diagnosis involves complex, costly, and potentially invasive procedures...
Machine learning predicting mortality in sarcoidosis patients admitted for acute heart failure [0.03%]
机器学习预测因急性心力衰竭入院的结节病患者的死亡率
Qiying Dai,Akil A Sherif,Chengyue Jin et al.
Qiying Dai et al.
Background: Sarcoidosis with cardiac involvement, although rare, has a worse prognosis than sarcoidosis involving other organ systems. Objective: ...
Early preclinical experience of a mixed reality ultrasound system with active GUIDance for NEedle-based interventions: The GUIDE study [0.03%]
基于针头的介入手术中早期混合现实超声系统的临床前研究经验：GUIDE研究
David Bloom,Jamie N Colombo,Nathan Miller et al.
David Bloom et al.
Background: Use of ultrasound (US) to facilitate vascular access has increased compared to landmark-based procedures despite ergonomic challenges and need for extrapolation of 2-dimensional images to understand needle pos...
Letter from the Deputy Editor [0.03%]
副主编来信
Hamid Ghanbari
Hamid Ghanbari
Psychosocial measures in relation to smartwatch alerts for atrial fibrillation detection [0.03%]
智能手表心房颤动检测警报的相关心理社会指标
Andreas Filippaios,Khanh-Van T Tran,Jordy Mehawej et al.
Andreas Filippaios et al.
Enhancing convolutional neural network predictions of electrocardiograms with left ventricular dysfunction using a novel sub-waveform representation [0.03%]
基于新型子波形表示增强卷积神经网络对左心室功能不全心电图的预测能力
Hossein Honarvar,Chirag Agarwal,Sulaiman Somani et al.
Hossein Honarvar et al.
Background: Electrocardiogram (ECG) deep learning (DL) has promise to improve the outcomes of patients with cardiovascular abnormalities. In ECG DL, researchers often use convolutional neural networks (CNNs) and tradition...
Staff acceptability and patient usability of a self-screening kiosk for atrial fibrillation in general practice waiting rooms [0.03%]
一种在全科诊所候诊室放置的房颤自助筛查亭被医务人员和病人接受的程度研究
Kirsty McKenzie,Nicole Lowres,Jessica Orchard et al.
Kirsty McKenzie et al.
Background: Current Australian and European guidelines recommend opportunistic screening for atrial fibrillation (AF) among patients ≥65 years, but general practitioners (GPs) report time constraints as a major barrier t...