Increased life expectancy in most countries is a result of continuous improvements at all
levels, starting from medicine and public health services, environmental and personal …

This paper presents a new End-to-End Deep Learning method for heart diseases diagnosis
from single channel ECG signal. Motivated by the great efficiency and popularity of deep …

Cardiovascular disorders are often diagnosed using an electrocardiogram (ECG). It is a
painless method that mimics the cyclical contraction and relaxation of the heart's muscles …

This paper proposes a novel Deep Learning technique for ECG beats classification. Unlike
the traditional Deep Learning models, a new Multi-Scale Wavelet Convolutional Neural …

Medical diagnosis is the process of determining a patient's health condition by the
observation of symptoms and test results. Cardiovascular diseases are one of the most …

This paper puts forward a 1-D convolutional neural network (CNN) that exploits a novel
analysis of the correlation between the two leads of the noisy electrocardiogram (ECG) to …

Cardiovascular disease (CVD) is the most common class of chronic and life-threatening
diseases and, therefore, considered to be one of the main causes of mortality. The proposed …

Electrocardiogram (ECG) is an important tool used to analyze abnormal heart activity and
assess heart health, especially in remote cardiac health monitoring. Although deep learning …

Electrocardiogram (ECG) signals play critical roles in the clinical screening and diagnosis of
many types of cardiovascular diseases. Despite the fact that deep neural networks have …

The classification and identification of arrhythmias using ECG signals hold substantial
practical importance in the early prevention and detection of cardiac/cardiovascular …