Background The electrocardiogram (ECG) is one of the most commonly used diagnostic
tools in medicine and healthcare. Deep learning methods have achieved promising results …

Deep learning models have become a popular mode to classify electrocardiogram (ECG)
data. Investigators have used a variety of deep learning techniques for this application …

In combination with current sociological trends, the maturing development of Internet of
Things devices is projected to revolutionize healthcare. A network of body-worn sensors …

Remote monitoring devices, which can be worn or implanted, have enabled a more effective
healthcare for patients with periodic heart arrhythmia due to their ability to constantly monitor …

Biosensors are emerging as efficient (sensitive and selective) and affordable analytical
diagnostic tools for early-stage disease detection, as required for personalized health …

Background: The advancement of information and communication technologies and the
growing power of artificial intelligence are successfully transforming a number of concepts …

Cardiac disease is the leading cause of death worldwide. Cardiovascular diseases can be
prevented if an effective diagnostic is made at the initial stages. The ECG test is referred to …

The use of deep learning (DL) for the analysis and diagnosis of biomedical and health care
problems has received unprecedented attention in the last decade. The technique has …

Cardiovascular diseases are a leading cause of mortality globally. Electrocardiography
(ECG) still represents the benchmark approach for identifying cardiac irregularities …

Arrhythmia is a common class of Cardiovascular disease which is the cause for over 31% of
all death over the world, according to WHOs' report. Automatic detection and classification of …