Deep convolutional neural network application to classify the ECG arrhythmia
The ECG signal is such a substantial means to reflect all the electrical activities of the
cardiac system. Therefore, it is considered by the physician as the essential tools and …
cardiac system. Therefore, it is considered by the physician as the essential tools and …
Automated heartbeat classification based on deep neural network with multiple input layers
H Shi, C Qin, D Xiao, L Zhao, C Liu - Knowledge-Based Systems, 2020 - Elsevier
The arrhythmia is an important group of cardiovascular disease. Electrocardiogram (ECG) is
commonly used for detecting arrhythmias. Computer-aided diagnosis system can diagnose …
commonly used for detecting arrhythmias. Computer-aided diagnosis system can diagnose …
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
This article presents a new deep learning approach for cardiac arrhythmia (17 classes)
detection based on long-duration electrocardiography (ECG) signal analysis …
detection based on long-duration electrocardiography (ECG) signal analysis …
Detection of arrhythmia in 12-lead varied-length ECG using multi-branch signal fusion network
Y Dong, W Cai, L Qiu, Y Guo, Y Chen… - Physiological …, 2022 - iopscience.iop.org
Objective. Automatic detection of arrhythmia based on electrocardiogram (ECG) plays a
critical role in early prevention and diagnosis of cardiovascular diseases. With the increase …
critical role in early prevention and diagnosis of cardiovascular diseases. With the increase …
Arrhythmia detection using TQWT, CEEMD and deep CNN-LSTM neural networks with ECG signals
Cardiac arrhythmia is a typically clinical manifestation of cardiovascular disease which leads
to serious health problem. Detection of arrhythmia is traditionally relying on manual …
to serious health problem. Detection of arrhythmia is traditionally relying on manual …
Single-layer convolution neural network for cardiac disease classification using electrocardiogram signals
P Gopika, CS Krishnendu, MH Chandana… - Deep learning for data …, 2020 - Elsevier
Medical diagnosis is the process of determining a patient's health condition by the
observation of symptoms and test results. Cardiovascular diseases are one of the most …
observation of symptoms and test results. Cardiovascular diseases are one of the most …
IM-ECG: An interpretable framework for arrhythmia detection using multi-lead ECG
R Tao, L Wang, Y Xiong, YR Zeng - Expert Systems with Applications, 2024 - Elsevier
Multi-lead electrocardiogram (ECG) is a fundamental and reliable diagnostic tool for the
detection of heart arrhythmias. An increasing number of deep neural network models have …
detection of heart arrhythmias. An increasing number of deep neural network models have …
A hybrid heartbeats classification approach based on marine predators algorithm and convolution neural networks
The electrocardiogram (ECG) is a non-invasive tool used to diagnose various heart
conditions. Arrhythmia is one of the primary causes of cardiac arrest. Early ECG beat …
conditions. Arrhythmia is one of the primary causes of cardiac arrest. Early ECG beat …
A high-precision arrhythmia classification method based on dual fully connected neural network
As an important arrhythmia detection method, the electrocardiogram (ECG) can directly
reflect abnormalities in cardiac physiological activity. In view of the difficulty in the diagnosis …
reflect abnormalities in cardiac physiological activity. In view of the difficulty in the diagnosis …
Cardiac arrhythmia detection using deep learning approach and time frequency representation of ECG signals
YD Daydulo, BL Thamineni, AA Dawud - BMC Medical Informatics and …, 2023 - Springer
Background Cardiac arrhythmia is a cardiovascular disorder characterized by disturbances
in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically …
in the heartbeat caused by electrical conduction anomalies in cardiac muscle. Clinically …