Deep Learning (DL) has recently become a topic of study in different applications including
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …

In contemporary day, Deep Learning (DL) is a developing discipline in the science of
Machine Learning (ML)(ML). The research in this field is evolving extremely fast and its …

Cardiovascular diseases are a leading cause of mortality globally. Electrocardiography
(ECG) still represents the benchmark approach for identifying cardiac irregularities …

Cardiovascular diseases affect approximately 50 million people worldwide; thus, heart
disease prevention is one of the most important tasks of any health care system. Despite the …

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 …

According to the World Health Organization (WHO) report, heart disease is spreading
throughout the world very rapidly and the situation is becoming alarming in people aged 40 …

Deep learning methods have shown early progress in analyzing complicated ECG signals,
especially in heartbeat classification and arrhythmia detection. However, there is still a long …

In this paper, an intellectual based electrocardiogram (ECG) signal classification approach
utilizing Deep Learning (DL) is being developed. ECG plays important role in diagnosing …

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 …

Cardiac arrhythmia is a condition where heart beat is irregular. The goal of this paper is to
apply deep learning techniques in the diagnosis of cardiac arrhythmia using ECG signals …