Atrial fibrillation (AF) is the most common arrhythmia with a high burden of morbidity
including impaired quality of life and increased risk of thromboembolism. Early detection and …

Atrial Fibrillation (AF) is the most studied cardiac arrhythmias due to its increasing
prevalence in today's scenario. Application of Artificial Intelligence (AI) for early identification …

Background: Atrial fibrillation (AF) is a common arrhythmia that can result in adverse
cardiovascular outcomes but is often difficult to detect. The use of machine learning (ML) …

AF is the most common clinically relevant cardiac arrhythmia associated with multiple
comorbidities, cardiovascular complications (eg stroke) and increased mortality. As artificial …

Atrial fibrillation (AF) affects more than 30 million individuals worldwide, making it the most
prevalent cardiac arrhythmia on a global scale. This systematic review summarizes recent …

Atrial fibrillation (AF) is a common arrhythmia affecting 8–10% of the population older than
80 years old. The importance of early diagnosis of atrial fibrillation has been broadly …

Background Atrial fibrillation (AF) is the most prevalent cardiac arrhythmia in the world. AF
increases the risk of stroke 5-fold, though the risk can be reduced with appropriate treatment …

Background Atrial fibrillation (AF) may occur asymptomatically and can be diagnosed only
with electrocardiography (ECG) while the arrhythmia is present. Objectives The aim of this …

Cardiovascular and neurological diseases are a major cause of mortality and morbidity
worldwide. Such diseases require careful monitoring to effectively manage their …

Background Recently, smart devices have been used for medical purposes, particularly to
screen for atrial fibrillation. However, current data on the diagnostic performance of these …