Hierarchical deep learning with Generative Adversarial Network for automatic cardiac diagnosis from ECG signals
Cardiac disease is the leading cause of death in the US. Accurate heart disease detection is
critical to timely medical treatment to save patients' lives. Routine use of the …
critical to timely medical treatment to save patients' lives. Routine use of the …
A novel temporal generative adversarial network for electrocardiography anomaly detection
Cardiac abnormality detection from Electrocardiogram (ECG) signals is a common task for
cardiologists. To facilitate efficient and objective detection, automated ECG classification by …
cardiologists. To facilitate efficient and objective detection, automated ECG classification by …
Generalization of convolutional neural networks for ECG classification using generative adversarial networks
Electrocardiograms (ECGs) play a vital role in the clinical diagnosis of heart diseases. An
ECG record of the heart signal over time can be used to discover numerous arrhythmias. Our …
ECG record of the heart signal over time can be used to discover numerous arrhythmias. Our …
Deep Learning‐Based Data Augmentation and Model Fusion for Automatic Arrhythmia Identification and Classification Algorithms
S Ma, J Cui, W Xiao, L Liu - Computational Intelligence and …, 2022 - Wiley Online Library
Automated ECG‐based arrhythmia detection is critical for early cardiac disease prevention
and diagnosis. Recently, deep learning algorithms have been widely applied for arrhythmia …
and diagnosis. Recently, deep learning algorithms have been widely applied for arrhythmia …
HeartNet: Self multihead attention mechanism via convolutional network with adversarial data synthesis for ECG-based arrhythmia classification
Cardiovascular disease is now one of the leading causes of morbidity and mortality.
Electrocardiogram (ECG) is a reliable tool for monitoring the health of the cardiovascular …
Electrocardiogram (ECG) is a reliable tool for monitoring the health of the cardiovascular …
Pgans: Personalized generative adversarial networks for ecg synthesis to improve patient-specific deep ecg classification
T Golany, K Radinsky - Proceedings of the AAAI Conference on Artificial …, 2019 - aaai.org
The Electrocardiogram (ECG) is performed routinely by medical personnel to identify
structural, functional and electrical cardiac events. Many attempts were made to automate …
structural, functional and electrical cardiac events. Many attempts were made to automate …
ECG arrhythmias detection using auxiliary classifier generative adversarial network and residual network
This paper aims at proposing an abnormality detection framework for electrocardiogram
(ECG) signals, which owns unbalance distribution among different classes and gaining high …
(ECG) signals, which owns unbalance distribution among different classes and gaining high …
SLC-GAN: An automated myocardial infarction detection model based on generative adversarial networks and convolutional neural networks with single-lead …
Electrocardiography (ECG) is a sophisticated tool for the diagnosis of myocardial infarction
(MI). Deep learning approaches can support MI diagnosis based on ECG data. However …
(MI). Deep learning approaches can support MI diagnosis based on ECG data. However …
Improving ECG classification using generative adversarial networks
The Electrocardiogram (ECG) is performed routinely by medical personell to identify
structural, functional and electrical cardiac events. Many attempts were made to automate …
structural, functional and electrical cardiac events. Many attempts were made to automate …
Generative adversarial network with transformer generator for boosting ECG classification
Y Xia, Y Xu, P Chen, J Zhang, Y Zhang - Biomedical Signal Processing and …, 2023 - Elsevier
Arrhythmia is an important group of cardiovascular diseases, which can suddenly attack and
cause sudden death, or continue to affect the heart and cause its failure. Electrocardiogram …
cause sudden death, or continue to affect the heart and cause its failure. Electrocardiogram …