Deep learning in ECG diagnosis: A review
X Liu, H Wang, Z Li, L Qin - Knowledge-Based Systems, 2021 - Elsevier
Cardiovascular disease (CVD) is a general term for a series of heart or blood vessels
abnormality that serves as a global leading reason for death. The earlier the abnormal heart …
abnormality that serves as a global leading reason for death. The earlier the abnormal heart …
[HTML][HTML] A review on deep learning methods for ECG arrhythmia classification
Z Ebrahimi, M Loni, M Daneshtalab… - Expert Systems with …, 2020 - Elsevier
Deep Learning (DL) has recently become a topic of study in different applications including
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
healthcare, in which timely detection of anomalies on Electrocardiogram (ECG) can play a …
An efficient ECG arrhythmia classification method based on Manta ray foraging optimization
The Electrocardiogram (ECG) arrhythmia classification has become an interesting research
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
area for researchers and developers as it plays a vital role in early prevention and diagnosis …
An automatic arrhythmia classification model based on improved marine predators algorithm and convolutions neural networks
Abstract Preparation of Convolutional Neural Networks (CNNs) for classification purposes
depends heavily on the knowledge of hyper-parameters tuning. This study aims, in particular …
depends heavily on the knowledge of hyper-parameters tuning. This study aims, in particular …
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 …
Enhancing dynamic ECG heartbeat classification with lightweight transformer model
Arrhythmia is a common class of Cardiovascular disease which is the cause for over 31% of
all death over the world, according to WHOs' report. Automatic detection and classification of …
all death over the world, according to WHOs' report. Automatic detection and classification of …
Review of deep learning-based atrial fibrillation detection studies
Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and
premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming …
premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming …
Cardiac arrhythmia classification using tunable Q-wavelet transform based features and support vector machine classifier
CK Jha, MH Kolekar - Biomedical Signal Processing and Control, 2020 - Elsevier
Electrocardiogram (ECG) is a non-invasive clinical tool that reveals the rhythm and
functionality of the human heart. It is widely used in the diagnosis of heart diseases including …
functionality of the human heart. It is widely used in the diagnosis of heart diseases including …
A deep learning approach for atrial fibrillation signals classification based on convolutional and modified Elman neural network
J Wang - Future Generation Computer Systems, 2020 - Elsevier
Atrial fibrillation (AF) is one of the main causes of life-threatening heart disease. Its detection
and diagnosis have been highly concerned by physicians in recent years. However, the …
and diagnosis have been highly concerned by physicians in recent years. However, the …
A novel unsupervised domain adaptation framework based on graph convolutional network and multi-level feature alignment for inter-subject ECG classification
Electrocardiogram (ECG) is an effective non-invasive tool that can detect arrhythmias.
Recently, deep learning (DL) has been widely used in ECG classification algorithms …
Recently, deep learning (DL) has been widely used in ECG classification algorithms …