Cardiovascular disease (CVD) is a general term for a series of heart or blood vessels
abnormality that serves as a global leading reason for death. The earlier the abnormal heart …

Objective: Rapid advances of high-throughput technologies and wide adoption of electronic
health records (EHRs) have led to fast accumulation of–omic and EHR data. These …

Cardiovascular disease is a major global public health problem, and intelligent diagnostic
approaches play an increasingly important role in the analysis of electrocardiograms …

Classification is one of the most popular topics in healthcare and bioinformatics, especially
in relation to arrhythmia detection. Arrhythmias are irregularities in the rate or rhythm of the …

This paper introduces a novel deep learning-based algorithm that integrates a long short-
term memory (LSTM)-based auto-encoder (AE) network with support vector machine (SVM) …

An electrocardiogram (ECG) measures the electric activity of the heart and has been widely
used for detecting heart diseases due to its simplicity and non-invasive nature. By analyzing …

We present a fully automatic and fast ECG arrhythmia classifier based on a simple brain-
inspired machine learning approach known as Echo State Networks. Our classifier has a low …

Detecting and classifying cardiac arrhythmias is critical to the diagnosis of patients with
cardiac abnormalities. In this paper, a novel approach based on deep learning methodology …

In this paper, we propose a novel approach based on deep learning for active classification
of electrocardiogram (ECG) signals. To this end, we learn a suitable feature representation …

The heart disease is one of the most serious health problems in today's world. Over 50
million persons have cardiovascular diseases around the world. Our proposed work based …