Atrial fibrillation (AF) is the most common cardiac arrhythmias causing morbidity and
mortality. AF may appear as episodes of very short (ie, proximal AF) or sustained duration …

Background Atrial fibrillation (AF) is the most common cardiac arrhythmia. The incidence of
AF increases with age, causing high risks of stroke and increased morbidity and mortality …

Goal: To develop a robust and real-time approach for automatic detection of atrial fibrillation
(AF) in long-term electrocardiogram (ECG) recordings using deep learning (DL). Method: An …

The most prevalent arrhythmia observed in clinical practice is atrial fibrillation (AF). AF is
associated with an irregular heartbeat pattern and a lack of a distinct P-waves signal. A low …

The automatic detection of atrial fibrillation (AF) is crucial for its association with the risk of
embolic stroke. Most of the existing AF detection methods usually convert 1D time-series …

Background Generalization model capacity of deep learning (DL) approach for atrial
fibrillation (AF) detection remains lacking. It can be seen from previous researches, the DL …

Atrial fibrillation (AF) is the most prevalent arrhythmia and is associated with increased
morbidity and mortality. Its early detection is challenging because of the low detection yield …

Atrial fibrillation (AF) can cause a variety of heart diseases and its detection is insufficient in
outside hospital. We proposed three methods for AF diagnosis in ambulatory settings. The …

Atrial fibrillation (AF) is one of the most common sustained chronic cardiac arrhythmia in
elderly population, associated with a high mortality and morbidity in stroke, heart failure …

Atrial fibrillation (AF) is the most common heart arrhythmia, and 12-lead electrocardiogram
(ECG) is regarded as the gold standard for AF diagnosis. Highly accurate diagnosis of AF …