Cardiac arrhythmias are one of the main causes of death worldwide; therefore, early
detection is essential to save the lives of patients who suffer from them and to reduce the …

This study introduces a new classifier tailored to address the limitations inherent in
conventional classifiers such as K-nearest neighbor (KNN), random forest (RF), decision …

As universal expressions to describe complex systems, graphs are increasingly preferred as
a representation method in artificial intelligence. Visibility graphs enable converting time …

The early and accurate detection of COVID-19 is vital nowadays to avoid the vast and rapid
spread of this virus and ease lockdown restrictions. As a result, researchers developed …

The supremacy of deep learning in artificial intelligence (AI) contexts, including image and
speech recognition, computer vision, and medical imaging, among others, has established it …

Real-time data collection and pre-processing have enabled the recognition, realization, and
prediction of diseases by extracting and analysing the important features of physiological …

An arrhythmia happens when the electrical signals that organize the heartbeat do not work
accurately. Most cases of arrhythmias may increase the risk of stroke or cardiac arrest. As a …

Background The electrocardiogram (ECG) is a widely used diagnostic that observes the
heart activities of patients to ascertain a heart abnormality diagnosis. The artifacts or noises …

Arrhythmia, a frequently encountered and life-threatening cardiac disorder, can manifest as
a transient or isolated event. Traditional automatic arrhythmia detection methods have …

Wearable devices are often used to diagnose arrhythmia, but the electrocardiogram (ECG)
monitoring process generates a large amount of data, which will affect the detection speed …