Latest AI and machine learning research in arrhythmias for healthcare professionals.
Among the various physiological signals, electrocardiogram (ECG) is a valid criterion for the classi...
Deep neural networks have become increasingly popular for analyzing ECG data because of their abilit...
Deep neural networks (DNNs) are increasingly important in the medical diagnosis of electrocardiogram...
Developing an efficient heartbeat monitoring system has become a focal point in numerous healthcare ...
BACKGROUND: Electrocardiogram (ECG) abnormalities have demonstrated potential as prognostic indicato...
Reliable classification of sleep stages is crucial in sleep medicine and neuroscience research for p...
The early identification of vulnerable patients has the potential to improve outcomes but poses a su...
Preclinical management of patients with acute chest pain and their identification as candidates for ...
BACKGROUND: Sinus node dysfunction because of abnormal impulse generation or sinoatrial conduction b...
One of the most common causes of death worldwide is heart disease, including arrhythmia. Today, scie...
The abnormal heart conduction, known as arrhythmia, can contribute to cardiac diseases that carry th...
Inherited arrhythmia disorders account for a significant proportion of sudden cardiac death, particu...
BACKGROUND: Electrocardiograms (ECG) are an important source of information on human heart health an...
Sleep apnoea is a common disorder affecting sleep quality by obstructing the respiratory airway. Thi...
ECG classification or heartbeat classification is an extremely valuable tool in cardiology. Deep lea...
The suprachiasmatic nucleus (SCN) is the mammalian central circadian pacemaker with heterogeneous ne...
BACKGROUND AND OBJECTIVE: Current automatic electrocardiogram (ECG) diagnostic systems could provide...
Biological age may be a more valuable predictor of morbidity and mortality than a person's chronolog...
Myocardial infarction (MI) is a common cardiovascular disease caused by the blockages of coronary ar...
BACKGROUND: Convolutional neural networks (CNNs) have emerged as a novel method for evaluating heart...
The efficacy of convolutional neural network (CNN)-enhanced electrocardiography (ECG) in detecting h...