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 …

Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

Electrocardiogram (ECG) is one among the most common detecting techniques in the
analysis and detection of cardiac arrhythmia adopted due to its cost efficiency and simplicity …

Computerized electrocardiogram (ECG) interpretation plays a critical role in the clinical ECG
workflow. Widely available digital ECG data and the algorithmic paradigm of deep learning …

Deep learning models have become a popular mode to classify electrocardiogram (ECG)
data. Investigators have used a variety of deep learning techniques for this application …

Early detection of arrhythmia and effective treatment can prevent deaths caused by
cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the …

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 …

Arrhythmia is an abnormal heartbeat rhythm, and its prevalence increases with age. An
electrocardiogram (ECG) is a standard tool for detecting cardiac activity. However, because …

Deep Learning (DL), a successful promising approach for discriminative and generative
tasks, has recently proved its high potential in 2D medical imaging analysis; however …

Artificial intelligence (AI) is increasingly used in electrocardiography (ECG) to assist in
diagnosis, stratification, and management. AI algorithms can help clinicians in the following …