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 …

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 …

The electrocardiogram (ECG) is one of the most widely used diagnostic instruments in
medicine and healthcare. Deep learning methods have shown promise in healthcare …

This article presents a new deep learning approach for cardiac arrhythmia (17 classes)
detection based on long-duration electrocardiography (ECG) signal analysis …

Electrocardiogram (ECG) is the most common and low‐cost diagnostic tool used in
healthcare institutes for screening heart electrical signals. The abnormal heart signals are …

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 …

Electrocardiogram (ECG) signals are the best way to monitor the functionality and health of
the cardiovascular system and also identify ailments related to it. Abnormal heartbeats are …

Classification is one of the most popular topics in healthcare and bioinformatics, especially
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …

Due to its simplicity and low cost, analyzing an electrocardiogram (ECG) is the most
common technique for detecting cardiac arrhythmia. The massive amount of ECG data …

An electrocardiogram (ECG) is an important diagnostic tool for the assessment of cardiac
arrhythmias in clinical routine. In this study, a deep learning framework previously trained on …