Atrial fibrillation (AF) is the most common sustained arrhythmia in the population and is
associated with a significant clinical and economic burden. Rigorous assessment of the …

In recent years, numerous applications for artificial intelligence (AI) in cardiology have been
found, due in part to large digitized data sets and the evolution of high-performance …

Deep learning (DL) has achieved promising performance in detecting common
abnormalities from the 12-lead electrocardiogram (ECG). However, diagnostic redundancy …

Background: Remodeling due to myocardial infarction (MI) significantly increases patient
arrhythmic risk. Simulations using patient-specific models have shown promise in predicting …

With the development of deep learning-based methods, automated classification of
electrocardiograms (ECGs) has recently gained much attention. Although the effectiveness …

With the development of deep learning-based methods, automated classification of
electrocardiograms (ECGs) has recently gained much attention. Although the effectiveness …

Background: We previously developed a non-invasive approach to localize the site of early
left ventricular activation origin in real time using 12-lead ECG, and to project the predicted …

The 12-lead ECG only has 8 independent ECG leads, which leads to diagnostic redundancy
when using all 12 leads for heart arrhythmias classification. We have previously developed …

Digital Technologies: Revolutionizing Cardiovascular Medicine and Reshaping the World Digital
Technologies: Revolutionizing Cardiovascular Medicine and Reshaping the World Can J Cardiol …

Efforts to automate the analysis of electrocardiograms (ECGs) date back to the 1950s when
researchers first converted ECG signals from analog to digital form, enabling the subsequent …