Background Atrial fibrillation (AF) is the arrhythmia most commonly diagnosed in clinical
practice. It is associated with significant morbidity and mortality. Prevalence of AF and …

Background: Risk prediction models for atrial fibrillation (AF) do not give information about
when AF might develop. Restricted mean survival time (RMST) quantifies risk into the time …

Introduction Atrial fibrillation (AF) is the most prevalent arrhythmia in the world and it is
associated with a high rate of cardiovascular morbidity and mortality. A higher burden of …

Studies investigating risk factors associated with atrial fibrillation (AF) have mostly focused
on AF presence and burden, disregarding the temporal distribution of AF episodes although …

The mechanism of atrial fibrillation (AF) maintenance in humans is yet to be determined. It
remains controversial whether cardiac fibrillatory dynamics are the result of a deterministic …

The purpose of the present study is to introduce a point process model for characterizing the
pattern of atrial fibrillation (AF) episodes. A variant of the bivariate Hawkes process is …

Background Detailed, patient-specific simulations of Atrial Fibrillation (AF) can simulate the
effect of potential therapies, although this requires adapting mathematical models to …

Atrial biophysical simulations have the potential to enhance outcomes by enabling the
simulation of pharmacological and ablative strategies. However, the high computational …

Atrial fibrillation (AF) is a complex cardiac arrhythmia with diverse etiology that negatively
affects morbidity and mortality of millions of patients. Technological and experimental …

(1) Background: Atrial fibrillation (AF) is a major risk factor for stroke and is often
underdiagnosed, despite being present in 13–26% of ischemic stroke patients. Recently, a …