Deep learning has become the method of choice to tackle real-world problems in different
domains, partly because of its ability to learn from data and achieve impressive performance …

Deep learning (DL) has been introduced in automatic heart-abnormality classification using
ECG signals, while its application in practical medical procedures is limited. A systematic …

Arrhythmias are defined as irregularities in the heartbeat rhythm, which may infrequently
occur in a human's life. These arrhythmias may cause potentially fatal complications, which …

An automatic system for heart arrhythmia classification can perform a substantial role in
managing and treating cardiovascular diseases. In this paper, a deep learning-based multi …

Cardiac arrhythmias, deviations from the normal rhythmic beating of the heart, are subtle yet
critical indicators of potential cardiac challenges. Efficiently diagnosing them requires …

Artificial intelligence (AI) continues to transform data analysis in many domains. Progress in
each domain is driven by a growing body of annotated data, increased computational …

Researchers have proposed numerous novel features and models under the intra-patient
paradigm. However, their performance suffers when considering the inter-patient paradigm …

The Electrocardiogram (ECG) remains a fundamental tool in cardiac diagnostics, yet its
interpretation has traditionally relied on cardiologists' expertise. Deep learning has …

Arrhythmia is a common type of cardiovascular disease, which has become the leading
cause of global deaths. Recently, automatic 12-lead ECG diagnosis system based on …

Electrocardiogram (ECG) signals are often used to diagnose cardiac status. However, most
of the existing ECG diagnostic methods only use the time-domain information, resulting in …