The success of deep learning over the traditional machine learning techniques in handling
artificial intelligence application tasks such as image processing, computer vision, object …

Abstract Cardiovascular diseases (CVDs) in India and globally are the major cause of
mortality, as revealed by the World Health Organization (WHO). The irregularities in the pace …

This research presents a comparison study between different representations of
spectrograms and then feeding them to different convolutional neural network (CNN) …

Electrocardiogram (ECG) is an important tool used to analyze abnormal heart activity and
assess heart health, especially in remote cardiac health monitoring. Although deep learning …

Cardiovascular health-related problem is a rapidly increasing integrated field concerning the
processing and fetching the information from cardiovascular systems for early detection and …

Nowadays, heart disease is the leading cause of death. The high mortality rate and
escalating occurrence of heart diseases worldwide warrant the requirement for a fast and …

Cardiac arrhythmias impose a significant burden on the healthcare environment due to the
increasing ratio of mortality worldwide. Arrhythmia and abnormal ECG heartbeat are the …

This article focuses on ECG signal recognition based on acoustic feature extraction
techniques. The SVM and k-NN classification approaches are proposed for recognizing the …

The main objective of this paper is to develop an interactive classifier aided deep learning
system to assist cardiologists for heart arrhythmia disease classification as it shows a health …

It is shown that the use of the representation of digital signals varying in the restricted
amplitude range through elements of Galois fields and the Galois field Fourier transform …