Recently, much effort has been put into solving arrhythmia classification problems with
machine learning-based methods. However, inter-heartbeat dependencies have been …

Arrhythmia was one of the primary causes of morbidity and mortality among cardiac patients.
Early diagnosis was essential in providing intervention for patients suffering from cardiac …

All over the world, time series‐based anomaly prediction plays a vital role in all walks of life
such as medical monitoring in hospitals and climate and environment risks. In the present …

In this paper, we propose an end-to-end deep learning architecture, referred as MCG-Net,
integrating convolutional neural network (CNN) with transformer-based global context block …

Myocardial infarction (MI) and cardiac arrhythmias remain leading causes of mortality within
cardiovascular diseases. Accurate and timely diagnosis using electrocardiogram (ECG) …

Cardiovascular disease continues to be one of the most prevalent medical conditions in
modern society, especially among elderly citizens. As the leading cause of deaths …

Heart failure is a leading cause of sudden unexpected death, especially among middle-
aged and elderly people. Analog electrocardiogram (ECG) signals are conventionally used …

Electrocardiogram (ECG) recordings are vital for diagnosing cardiac abnormalities like
arrhythmias, crucial in managing cardiovascular diseases (CVD). However, manual analysis …

An ECG, also known as an electrocardiogram, gauges the electrical movements within the
heart. It has been commonly utilized for identifying heart illnesses because of its …

Cardiovascular disease continues to be one of the most prevalent medical conditions in
modern society, especially among elderly citizens. This thesis reviewed the challenges of …