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 …
Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals
Myocardial infarction (MI) accounts for a high number of deaths globally. In acute MI,
accurate electrocardiography (ECG) is important for timely diagnosis and intervention in the …
accurate electrocardiography (ECG) is important for timely diagnosis and intervention in the …
Myocardial infarction detection based on deep neural network on imbalanced data
Myocardial infarction (MI) is an acute interruption of blood flow to the heart, which causes the
heart to suffer from a deficiency of blood and ischemia, so the heart muscle is damaged, and …
heart to suffer from a deficiency of blood and ischemia, so the heart muscle is damaged, and …
Deep learning for detecting and locating myocardial infarction by electrocardiogram: A literature review
P Xiong, SMY Lee, G Chan - Frontiers in cardiovascular medicine, 2022 - frontiersin.org
Myocardial infarction is a common cardiovascular disorder caused by prolonged ischemia,
and early diagnosis of myocardial infarction (MI) is critical for lifesaving. ECG is a simple and …
and early diagnosis of myocardial infarction (MI) is critical for lifesaving. ECG is a simple and …
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 …
MSGformer: A multi-scale grid transformer network for 12-lead ECG arrhythmia detection
C Ji, L Wang, J Qin, L Liu, Y Han, Z Wang - Biomedical Signal Processing …, 2024 - Elsevier
The electrocardiogram (ECG) is a ubiquitous medical diagnostic tool employed to identify
arrhythmias that are characterized by anomalous waveform morphology and erratic …
arrhythmias that are characterized by anomalous waveform morphology and erratic …
Accurate detection of myocardial infarction using non linear features with ECG signals
Interrupted blood flow to regions of the heart causes damage to heart muscles, resulting in
myocardial infarction (MI). MI is a major source of death worldwide. Accurate and timely …
myocardial infarction (MI). MI is a major source of death worldwide. Accurate and timely …
CNN-KCL: Automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering
D Sharifrazi, R Alizadehsani… - Mathematical …, 2022 - researchers.mq.edu.au
Myocarditis is the form of an inflammation of the middle layer of the heart wall which is
caused by a viral infection and can affect the heart muscle and its electrical system. It has …
caused by a viral infection and can affect the heart muscle and its electrical system. It has …