The prevalence of cardiovascular diseases is increasing around the world. However, the
technology is evolving and can be monitored with low-cost sensors anywhere at any time …

Contemporary methods used to interpret the electrocardiogram (ECG) signal for diagnosis
or monitoring are based on expert knowledge and rule-centered algorithms. In recent years …

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

Abstract Background and Objective Effectively assessing the coronary stenosis degree is
vital for the diagnosis of coronary artery disease (CAD). Electrocardiogram (ECG) and …

Patients with atrial fibrillation (AF) are prone to complications such as heart failure with
preserved ejection fraction (HFpEF), which accelerates the progress of the disease and can …

Accurate classification of congestive heart failure (CHF) is essential to reduce the mortality of
cardiovascular disease. Many existing researches suffer from unsatisfactory performance in …

Heart diseases impact disproportionately the low-income portion of any society. The lack of
a sufficient number of physicians as well as expensive diagnostic procedures brings forth …

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

Heart failure (HF) diagnosis, typically visually performed by serial electrocardiography, may
be supported by machine-learning approaches. Repeated structuring & learning procedure …

Objectives Arrhythmia is an important component of cardiovascular disease, and
electrocardiogram (ECG) is a method to detect arrhythmia. Arrhythmia detection is often …