This paper introduces a novel deep learning model for ECG signal classification using
feature fusion. The proposed methodology transforms the ECG time series into a …

Abstract “I see, I forget, I read aloud, I remember, and when I do read purposefully by writing
it, I do not forget it.” This phenomenon is known as “interoception” and refers to the sensing …

Cardiovascular disease (CVD) is connected with irregular cardiac electrical activity, which
can be seen in ECG alterations. Due to its convenience and non-invasive aspect, the ECG is …

Congestive heart failure (CHF) is a serious threat to human health. Electrocardiogram (ECG)
signals have been proven to be useful in the detection of CHF. However, the low amplitude …

Although healthcare and medical technology have advanced significantly over the past few
decades, heart disease continues to be a major cause of mortality globally …

Throughout recorded history, cardiovascular diseases have posed a persistent threat,
claiming numerous lives. Effective and timely testing is pivotal in preventing fatalities. Among …

Applying deep neural networks with stacked denoising autoencoders (SDAEs) for ECG
signal classification presents a promising approach for improving the accuracy of arrhythmia …

Advances in medical imaging and Artificial Intelligence (AI) have ushered in an era of
possibilities in healthcare. The number of imaging studies is naturally increasing, and so …

Cardiovascular disease, also referred to as heart disease, is a common chronic illness that
affects people all over the world. It continues to be a major global cause of death. Timely …