Valvular heart disease is a major cause of morbidity and mortality worldwide. Surgical valve
repair or replacement has been the standard of care for patients with valvular heart disease …

Mathematical modeling and simulation are moving from being powerful development and
analysis tools towards having increased roles in operational monitoring, control and …

Abstract Background and Objective: Cardiac electrophysiology is a medical specialty with a
long and rich tradition of computational modeling. Nevertheless, no community standard for …

Artificial intelligence (AI) and machine learning (ML) in medicine are currently areas of
intense exploration, showing potential to automate human tasks and even perform tasks …

Machine learning (ML), a branch of artificial intelligence, where machines learn from big
data, is at the crest of a technological wave of change swee** society. Cardiovascular …

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

Background: Current ablation therapy for atrial fibrillation is suboptimal, and long-term
response is challenging to predict. Clinical trials identify bedside properties that provide only …

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

The complexity of cardiac electrophysiology, involving dynamic changes in numerous
components across multiple spatial (from ion channel to organ) and temporal (from …

We aim to provide a critical appraisal of basic concepts underlying signal recording and
processing technologies applied for (i) atrial fibrillation (AF) map** to unravel AF …