Deep learning-based ECG arrhythmia classification: A systematic review
Deep learning (DL) has been introduced in automatic heart-abnormality classification using
ECG signals, while its application in practical medical procedures is limited. A systematic …
ECG signals, while its application in practical medical procedures is limited. A systematic …
Deep learning for ECG Arrhythmia detection and classification: an overview of progress for period 2017–2023
Cardiovascular diseases are a leading cause of mortality globally. Electrocardiography
(ECG) still represents the benchmark approach for identifying cardiac irregularities …
(ECG) still represents the benchmark approach for identifying cardiac irregularities …
An overview on state-of-the-art electrocardiogram signal processing methods: Traditional to AI-based approaches
VA Ardeti, VR Kolluru, GT Varghese… - Expert Systems with …, 2023 - Elsevier
Over the last decade, cardiovascular diseases (CVD's) are the leading cause of death
globally. Early prediction of CVD's can help in reducing the complications of high-risk …
globally. Early prediction of CVD's can help in reducing the complications of high-risk …
[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
Application of dense neural networks for detection of atrial fibrillation and ranking of augmented ECG feature set
Considering the significant burden to patients and healthcare systems globally related to
atrial fibrillation (AF) complications, the early AF diagnosis is of crucial importance. In the …
atrial fibrillation (AF) complications, the early AF diagnosis is of crucial importance. In the …
Hierarchical online contrastive anomaly detection for fetal arrhythmia diagnosis in ultrasound
Arrhythmia is a major cardiac abnormality in fetuses. Therefore, early diagnosis of
arrhythmia is clinically crucial. Pulsed-wave Doppler ultrasound is a commonly used …
arrhythmia is clinically crucial. Pulsed-wave Doppler ultrasound is a commonly used …
Artificial intelligence for atrial fibrillation detection, prediction, and treatment: A systematic review of the last decade (2013–2023)
Atrial fibrillation (AF) affects more than 30 million individuals worldwide, making it the most
prevalent cardiac arrhythmia on a global scale. This systematic review summarizes recent …
prevalent cardiac arrhythmia on a global scale. This systematic review summarizes recent …
A shallow domain knowledge injection (sdk-injection) method for improving cnn-based ecg pattern classification
S Oh, M Lee - Applied sciences, 2022 - mdpi.com
Featured Application The proposed method can improve the accuracy of an existing
parameter-optimized CNN for ECG pattern classification. Especially, by applying the …
parameter-optimized CNN for ECG pattern classification. Especially, by applying the …
A light-weight deep residual network for classification of abnormal heart rhythms on tiny devices
R Banerjee, A Ghose - Joint European Conference on Machine Learning …, 2022 - Springer
An automatic classification of abnormal heart rhythms using electrocardiogram (ECG)
signals has been a popular research area in medicine. In spite of reporting good accuracy …
signals has been a popular research area in medicine. In spite of reporting good accuracy …
Hemodynamic functional connectivity optimization of frequency EEG microstates enables attention LSTM framework to classify distinct temporal cortical …
S Agrawal, V Chinnadurai, R Sharma - Brain Informatics, 2022 - Springer
Temporal analysis of global cortical communication of cognitive tasks in coarse EEG
information is still challenging due to the underlying complex neural mechanisms. This study …
information is still challenging due to the underlying complex neural mechanisms. This study …