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 …
A novel method for reducing arrhythmia classification from 12-lead ECG signals to single-lead ECG with minimal loss of accuracy through teacher-student knowledge …
M Sepahvand, F Abdali-Mohammadi - Information Sciences, 2022 - Elsevier
Deep learning models developed through multi-lead electrocardiogram (ECG) signals are
considered the leading methods for the automated detection of arrhythmia on computer …
considered the leading methods for the automated detection of arrhythmia on computer …
Diagnosis of arrhythmias with few abnormal ECG samples using metric-based meta learning
Z Liu, Y Chen, Y Zhang, S Ran, C Cheng… - Computers in biology and …, 2023 - Elsevier
A major challenge in artificial intelligence based ECG diagnosis lies that it is difficult to
obtain sufficient annotated training samples for each rhythm type, especially for rare …
obtain sufficient annotated training samples for each rhythm type, especially for rare …
Automatic cardiac arrhythmia classification based on hybrid 1-D CNN and Bi-LSTM model
Cardiovascular diseases (CVDs) are a group of heart and blood vessel ailments that can
cause chest pain and trouble breathing, especially while active. However, some patients …
cause chest pain and trouble breathing, especially while active. However, some patients …
ECG classification using 1-D convolutional deep residual neural network
An electrocardiograph (ECG) is widely used in diagnosis and prediction of cardiovascular
diseases (CVDs). The traditional ECG classification methods have complex signal …
diseases (CVDs). The traditional ECG classification methods have complex signal …
Exploring deep features and ECG attributes to detect cardiac rhythm classes
Arrhythmia is a condition characterized by perturbation of the regular rhythm of the heart.
The development of computerized self-diagnostic systems for the detection of these …
The development of computerized self-diagnostic systems for the detection of these …
Multilevel classification and detection of cardiac arrhythmias with high-resolution superlet transform and deep convolution neural network
Atrial fibrillation and ventricular fibrillation are the two most common cardiac arrhythmia.
These cardiac arrhythmias cause heart strokes and other heart complications leading to an …
These cardiac arrhythmias cause heart strokes and other heart complications leading to an …
Single-lead ECG recordings modeling for end-to-end recognition of atrial fibrillation with dual-path RNN
Atrial fibrillation (AF) is the most common type of sustained cardiac arrhythmia, and is
associated with stroke, coronary artery disease and mortality. Thus, early detection is crucial …
associated with stroke, coronary artery disease and mortality. Thus, early detection is crucial …
Novel automated PD detection system using aspirin pattern with EEG signals
Background and objective Parkinson's disease (PD) is one of the most common diseases
worldwide which reduces quality of life of patients and their family members. The …
worldwide which reduces quality of life of patients and their family members. The …
Multi-modal stacking ensemble for the diagnosis of cardiovascular diseases
T Yoon, D Kang - Journal of Personalized Medicine, 2023 - mdpi.com
Background: Cardiovascular diseases (CVDs) are a leading cause of death worldwide.
Deep learning methods have been widely used in the field of medical image analysis and …
Deep learning methods have been widely used in the field of medical image analysis and …