The field of cardiac electrophysiology (EP) had adopted simple artificial intelligence (AI)
methodologies for decades. Recent renewed interest in deep learning techniques has …

Despite significant advances in its detection, understanding and management, atrial
fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on …

Obesity is a well‐known risk factor for atrial fibrillation (AF). Local epi‐myocardial or intra‐
myocardial adiposity caused by aging, obesity, or cardiovascular disease (CVD) is …

In the heart, electrophysiological dysregulation arises from defects at many biological levels
(from point mutations in ion channel proteins to gross structural abnormalities). These …

In this article, the authors focus on the importance of the zero X-ray ablation approach in
electrophysiology. Radiation exposure related to conventional transcatheter ablation carries …

Personalized cardiac mechanics modeling is a powerful tool for understanding the
biomechanics of cardiac function in health and disease and assisting in treatment planning …

Mechanisms of atrial fibrillation and the susceptibility to reentries can be impacted by the
repolarization across the atria. Studies into atrial fibrillation ignore cell-to-cell heterogeneity …

Artificial intelligence through machine learning (ML) methods is becoming prevalent
throughout the world, with increasing adoption in healthcare. Improvements in technology …

Cardiac digital twins (CDTs) of human cardiac electrophysiology (EP) are digital replicas of
patient hearts that match like-for-like clinical observations. The electrocardiogram (ECG), as …

Atrial fibrillation (AF) is the commonest cardiac arrhythmia, affecting 3 million people in the
USA and 8 million in the EU (according to the European Society of Cardiology). So, why is it …