Monitoring heart electrical activity is an effective way of detecting existing and developing
conditions. This is usually performed as a non-invasive test using a network of up to 12 …

Cardiac arrhythmias, characterized by deviations from the normal rhythmic contractions of
the heart, pose a formidable diagnostic challenge. Early and accurate detection remains an …

Electrocardiography is essential for the early diagnosis and treatment of heart diseases, as
undiagnosed heart diseases can lead to unfortunate outcomes such as patient loss …

The classification of electrocardiogram (ECG) plays a crucial role in the development of an
automatic cardiovascular diagnostic system. However, the considerable variances in ECG …

As the global health care system grapples with steadily rising costs, increasing numbers of
admissions, and the chronic defection of doctors and nurses from the profession …

Predicting the blood–brain barrier (BBB) permeability of small-molecule compounds using a
novel artificial intelligence platform is necessary for drug discovery. Machine learning and a …

Obtaining information about the electrical activity of the heart in the form of
electrocardiograms (ECG) has become a standard way of monitoring patients' heart rhythm …

This study aims to address the need for reliable diagnosis of coronary artery disease (CAD)
using artificial intelligence (AI) models. Despite the progress made in mitigating opacity with …

Heart disease has been the leading cause of mortality worldwide in the recent decade.
Since 2019, new lung-related infections have increased heart attack mortality. To minimize …

In recent years, a wide variety of Machine Learning (ML) algorithms, including Deep
Learning (DL) methods, have been proposed for electrocardiogram (ECG) beat …