Computer modeling of the electrophysiology of the heart has undergone significant
progress. A healthy heart can be modeled starting from the ion channels via the spread of a …

Large-scale electrophysiological simulations to obtain electrocardiograms (ECG) carry the
potential to produce extensive datasets for training of machine learning classifiers to, eg …

Background Atrial fibrillation (AF) is accompanied by progressive epicardial fibrosis,
dissociation of electrical activity between the epicardial layer and the endocardial bundle …

The identification of patients prone to atrial fibrillation (AF) relapse after catheter ablation is
essential for better patient selection and risk stratification. The current prospective cohort …

Computer-based simulations of non-invasive cardiac electrophysiological outputs, such as
electrocardiograms and body surface potential maps, usually entail severe computational …

Computational models of atrial fibrillation (AF) can help improve success rates of
interventions, such as ablation. However, evaluating the efficacy of different treatments …

Cardiac electrophysiology modeling deals with a complex network of excitable cells forming
an intricate syncytium: the heart. The electrical activity of the heart shows recurrent spatial …

Background Sex-related electrocardiographic differences are a well-known phenomenon,
but not their expression in patients with atrial fibrillation (AF). In this study we aim to assess …

Early identification of patients at risk for paroxysmal atrial fibrillation (PAF) is essential to
attain optimal treatment and a favorable prognosis. We compared the performance of a beat …

Aims Recent clinical studies showed that antiarrhythmic drug (AAD) treatment and
pulmonary vein isolation (PVI) synergistically reduce atrial fibrillation (AF) recurrences after …