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 …
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 …
Automated detection of COVID-19 cases using deep neural networks with X-ray images
Abstract The novel coronavirus 2019 (COVID-2019), which first appeared in Wuhan city of
China in December 2019, spread rapidly around the world and became a pandemic. It has …
China in December 2019, spread rapidly around the world and became a pandemic. It has …
A survey on deep learning in medicine: Why, how and when?
New technologies are transforming medicine, and this revolution starts with data. Health
data, clinical images, genome sequences, data on prescribed therapies and results …
data, clinical images, genome sequences, data on prescribed therapies and results …
Designing ECG monitoring healthcare system with federated transfer learning and explainable AI
Deep learning plays a vital role in classifying different arrhythmias using
electrocardiography (ECG) data. Nevertheless, training deep learning models normally …
electrocardiography (ECG) data. Nevertheless, training deep learning models normally …
Deep MLP-CNN model using mixed-data to distinguish between COVID-19 and Non-COVID-19 patients
The limitations and high false-negative rates (30%) of COVID-19 test kits have been a
prominent challenge during the 2020 coronavirus pandemic. Manufacturing those kits and …
prominent challenge during the 2020 coronavirus pandemic. Manufacturing those kits and …
Automated ECG classification using a non-local convolutional block attention module
J Wang, X Qiao, C Liu, X Wang, YY Liu, L Yao… - Computer Methods and …, 2021 - Elsevier
Background and objective: Recent advances in deep learning have been applied to ECG
detection and obtained great success. The spatial and temporal information from ECG …
detection and obtained great success. The spatial and temporal information from ECG …
A novel automated CNN arrhythmia classifier with memory-enhanced artificial hummingbird algorithm
E Kıymaç, Y Kaya - Expert Systems with Applications, 2023 - Elsevier
Cardiac arrhythmias indicate cardiovascular disease which is the leading cause of mortality
worldwide, and can be detected by an electrocardiogram (ECG). Automated deep learning …
worldwide, and can be detected by an electrocardiogram (ECG). Automated deep learning …
Arrhythmia classification with ECG signals based on the optimization-enabled deep convolutional neural network
Arrhythmia classification is the need of the hour as the world is reporting a higher death troll
as a cause of cardiac diseases. Most of the existing methods developed for arrhythmia …
as a cause of cardiac diseases. Most of the existing methods developed for arrhythmia …
A smart decision support system to diagnose arrhythymia using ensembled ConvNet and ConvNet-LSTM model
Automatic screening approaches can help diagnose Cardiovascular Disease (CVD) early,
which is the leading source of mortality worldwide. Electrocardiogram (ECG/EKG)-based …
which is the leading source of mortality worldwide. Electrocardiogram (ECG/EKG)-based …