Transformer architectures have become increasingly popular in healthcare applications.
Through outstanding performance in natural language processing and superior capability to …

The rapid development of biosensing technologies together with the advent of deep learning
has marked an era in healthcare and biomedical research where widespread devices like …

Automatic analysis of electrocardiogram (ECG) signals is one of the applications in the
medical domain where deep learning methods demonstrate impressive performance …

Electrocardiography (ECG) is a crucial tool for diagnosing cardiovascular diseases. In
particular, combining clinical ECG with computer technology for automatic ECG analysis can …

Arrhythmia is a heart condition that poses a severe threat to life and requires prompt medical
attention. One of the challenges in detecting arrhythmias accurately is that incorrect …

Significant advances have been made in artificial intelligence technology in recent years.
Many health care applications have been investigated to assist clinicians and the …

Numerous researchers have developed electrocardiogram (ECG) classification systems to
automatically diagnose coronary artery disease (CAD) and congestive heart failure (CHF) …

Objective: Physiological signals, such as electrocardiogram (ECG) and wrist pulse signals
(WPS), play an important role in diagnosing and preventing cardiovascular and other …

A WGAN-GP-based ECG signal expansion and an SE-ResNet1D-based ECG classification
method are proposed to address the problem of poor modeling results due to the …

Atrial fibrillation (AFIB) and ventricular fibrillation (VFIB) are two common cardiovascular
diseases that cause numerous deaths worldwide. Medical staff usually adopt long-term …