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 …
Fully automatic electrocardiogram classification system based on generative adversarial network with auxiliary classifier
A generative adversarial network (GAN) based fully automatic electrocardiogram (ECG)
arrhythmia classification system with high performance is presented in this paper. The …
arrhythmia classification system with high performance is presented in this paper. The …
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 …
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 …
An effective data enhancement method for classification of ECG arrhythmia
S Ma, J Cui, CL Chen, X Chen, Y Ma - Measurement, 2022 - Elsevier
Our blood vessels show signs of aging as we grow older, which leads to various
cardiovascular diseases. Arrhythmia is usually the symptom of patients with early …
cardiovascular diseases. Arrhythmia is usually the symptom of patients with early …
ECG generation with sequence generative adversarial nets optimized by policy gradient
F Ye, F Zhu, Y Fu, B Shen - IEEE Access, 2019 - ieeexplore.ieee.org
Electrocardiogram (ECG) is a method used by physicians to detect cardiac disease.
Requirements for batch processing and accurate recognition of clinical data have led to the …
Requirements for batch processing and accurate recognition of clinical data have led to the …
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 …
CAB: classifying arrhythmias based on imbalanced sensor data
Intelligently detecting anomalies in health sensor data streams (eg, Electrocardiogram,
ECG) can improve the development of E-health industry. The physiological signals of …
ECG) can improve the development of E-health industry. The physiological signals of …
Electrocardiogram generation with a bidirectional LSTM-CNN generative adversarial network
F Zhu, F Ye, Y Fu, Q Liu, B Shen - Scientific reports, 2019 - nature.com
Heart disease is a malignant threat to human health. Electrocardiogram (ECG) tests are
used to help diagnose heart disease by recording the heart's activity. However, automated …
used to help diagnose heart disease by recording the heart's activity. However, automated …
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 …