… ventricular contraction (PVC) is an increasingly prevalent arrhythmia disease, which results
from the ectopic foci in ventricle … can lead to the malignant ventricular arrhythmia or other …

… A deep neural networks is proposed for the classification of premature ventricular contraction
(… In this paper, we propose an optimized deep neural networks for PVC beat classification. …

… to detect premature ventricular contractions (PVCs) using the neural network with weighted
… around the QRS complex that represents ventricular depolarization in the electrocardiogram (…

… Unlike traditional RNN, a LSTM network is well-suited to learn from experience to classify, …
We utilized LSTM network as base classifier in this paper. We used Theano-0.6rc [21], [22], …

… and ventricular premature contractions (PVCs) is paramount for accurate cardiac rhythm
assessment. This study introduces a novel application of the 1D U-Net neural network …

… throughout the ventricles by applying neural networks to 12-lead ECG. The ventricles are
divided into 25 segments based on standard myocardial segmentation of the left ventricle [26] …

… Premature ventricular contraction (PVC) is a common type of abnormal heartbeat. Without …
training a learning vector quantization (LVQ) neural network. Our algorithm can obtain a good …

… MobileNetV2 was the network that performed the best in both experiments among the
strategies utilized in this study and in comparison to the methodologies proposed in the literature. …

… In this paper, we presented quantum neural network and the experiments to apply it on
the automatic detection of premature ventricular contraction based on ECG recordings. …

… In this paper, we propose a nine-layer convolutional neural network (CNN) that can … ,
namely: normal beat (N), premature ventricular contraction beat (V), and right bundle branch block …