A novel approach for multi-lead ECG classification using DL-CCANet and TL-CCANet
W Yang, Y Si, D Wang, G Zhang - Sensors, 2019 - mdpi.com
Cardiovascular disease (CVD) has become one of the most serious diseases that threaten
human health. Over the past decades, over 150 million humans have died of CVDs. Hence …
human health. Over the past decades, over 150 million humans have died of CVDs. Hence …
Lightx3ecg: A lightweight and explainable deep learning system for 3-lead electrocardiogram classification
Cardiovascular diseases (CVDs) are a group of heart and blood vessel disorders that is one
of the most serious dangers to human health, and the number of such patients is still …
of the most serious dangers to human health, and the number of such patients is still …
PDNet: a convolutional neural network has potential to be deployed on small intelligent devices for arrhythmia diagnosis
F Yang, X Zhang, Y Zhu - Computer Modeling in Engineering & …, 2020 - ingentaconnect.com
Heart arrhythmia is a group of irregular heartbeat conditions and is usually detected by
electrocardiograms (ECG) signals. Over the past years, deep learning methods have been …
electrocardiograms (ECG) signals. Over the past years, deep learning methods have been …
ECG signal classification based on deep CNN and BiLSTM
J Cheng, Q Zou, Y Zhao - BMC medical informatics and decision making, 2021 - Springer
Background Currently, cardiovascular disease has become a major disease endangering
human health, and the number of such patients is growing. Electrocardiogram (ECG) is an …
human health, and the number of such patients is growing. Electrocardiogram (ECG) is an …
Automatic classification of arrhythmias using multi-branch convolutional neural networks based on channel-based attention and bidirectional LSTM
F Liu, H Li, T Wu, H Lin, C Lin, G Han - ISA transactions, 2023 - Elsevier
Cardiac arrhythmia is an abnormal rhythm of the heartbeat and can be life-threatening
Electrocardiogram (ECG) is a technology that uses an electrocardiograph machine to record …
Electrocardiogram (ECG) is a technology that uses an electrocardiograph machine to record …
Electrocardiogram Signals Classification Using Deep-Learning-Based Incorporated Convolutional Neural Network and Long Short-Term Memory Framework
A Eleyan, E Alboghbaish - Computers, 2024 - mdpi.com
Cardiovascular diseases (CVDs) like arrhythmia and heart failure remain the world's leading
cause of death. These conditions can be triggered by high blood pressure, diabetes, and …
cause of death. These conditions can be triggered by high blood pressure, diabetes, and …
Heartbeat classification and arrhythmia detection using a multi-model deep-learning technique
Cardiac arrhythmias pose a significant danger to human life; therefore, it is of utmost
importance to be able to efficiently diagnose these arrhythmias promptly. There exist many …
importance to be able to efficiently diagnose these arrhythmias promptly. There exist many …
A study on arrhythmia via ECG signal classification using the convolutional neural network
M Wu, Y Lu, W Yang, SY Wong - Frontiers in computational …, 2021 - frontiersin.org
Cardiovascular diseases (CVDs) are the leading cause of death today. The current
identification method of the diseases is analyzing the Electrocardiogram (ECG), which is a …
identification method of the diseases is analyzing the Electrocardiogram (ECG), which is a …
12-Lead ECG signal classification for detecting ECG arrhythmia via an information bottleneck-based multi-scale network
Abstract The 12-lead electrocardiogram (ECG) is a reliable diagnostic tool for detecting and
treating severe cardiovascular conditions like arrhythmia and heart attack. Deep neural …
treating severe cardiovascular conditions like arrhythmia and heart attack. Deep neural …
An arrhythmia classification model based on vision transformer with deformable attention
Y Dong, M Zhang, L Qiu, L Wang, Y Yu - Micromachines, 2023 - mdpi.com
The electrocardiogram (ECG) is a highly effective non-invasive tool for monitoring heart
activity and diagnosing cardiovascular diseases (CVDs). Automatic detection of arrhythmia …
activity and diagnosing cardiovascular diseases (CVDs). Automatic detection of arrhythmia …