Left bundle branch block (LBBB) is a common disorder in the heart's electrical conduction
system that leads to the ventricles' uncoordinated contraction. The complete LBBB is usually …

Heart disease should be treated quickly when symptoms appear. Machine-learning methods
for detecting heart disease require desktop computers, an obstacle that can have fatal …

Arrhythmia is the common disease in today's society. In order to judge the specific situation
of the patient, doctors often observe the ECG (Electrocardiograph) signal to get enough …

Electrocardiogram (ECG) and phonocardiogram (PCG) signals are physiological signals
generated throughout the cardiac cycle. The application of deep learning techniques to …

Atrial fibrillation (AF) and ventricular arrhythmia (Arr) are among the most common and fatal
cardiac arrhythmias in the world. Electrocardiogram (ECG) data, collected as part of the UK …

Most existing Electrocardiogram (ECG) classification methods assume that all arrhythmia
classes are known during the training phase. In this paper, the problem of learning several …

Automatic classification of ECG signals has become a research hotspot, and most of the
research work in this field is currently aimed at single-label classification. However, a …

Arrhythmias are a significant cause of morbidity and mortality worldwide, necessitating
accurate and timely detection for effective clinical intervention. Electrocardiogram (ECG) …

Vital sign monitoring is becoming a part of our daily lives, emerging as a trend of smart
wearable devices used to manage health. Cardiac arrhythmia is any variation in the normal …

Since irregular heartbeat symptoms arise, it's critical to accurately diagnose the patient's
heart problem. This research aims to use a training algorithm for disease detection. The …