… Abstract—Atrial Fibrillation (AF) the most commonly occurring type of cardiac arrhythmia is
one of the … n this paper, state-ofthe-art ECG data-based machine learning models and signal …

… of patients with already diagnosed atrial fibrillation, for example, by … machine learning
and, in particular, artificial neural networks in the detection and management of atrial fibrillation …

… The use of machine learning for predicting disease may enable physicians to speed-up …
of machine learning in various aspects of healthcare[15], we utilised machine learning …

… -learning machine learning methods, … of machine learning related to the care of AF thus far,
their potential future directions, and its potential limitations and challenges. Machine learning …

… The atrial fibrillation (AF) is one of the most well-known … We have implemented machine
learning and deep learning … The initial experimental results illustrate that the deep learning …

… that can predict the development of atrial fibrillation. These clinical parameters include previous
… of machine learning methodologies in the prediction and screening of atrial fibrillation as …

… Machine learning was able to classify complex intracardiac atrial fibrillation patterns as
accurately … within both atria in a 67-year-old woman with persistent atrial fibrillation (AF), showing …

… on training machine learning models to classify atrial fibrillation [16–19]. … atrial fibrillation.
Normal sinus rhythm contains a P-wave and displays regular beat timing while atrial fibrillation …

… There has been an exponential growth of artificial intelligence (AI) and machine learning (ML)
publications aimed at advancing our understanding of atrial fibrillation (AF), which has …

… Vector Machine (SVM) classifier. We used the Massachusetts Institute of Technology (MIT)—Beth
Israel Hospital (BIH) Atrial Fibrillation database and the MIT-BIH Arrhythmia database …