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 …
Generative adversarial networks in electrocardiogram synthesis: Recent developments and challenges
Training deep neural network classifiers for electrocardiograms (ECGs) requires sufficient
data. However, imbalanced datasets pose a major problem for the training process and …
data. However, imbalanced datasets pose a major problem for the training process and …
[HTML][HTML] Deep Generative Models: The winning key for large and easily accessible ECG datasets?
Large high-quality datasets are essential for building powerful artificial intelligence (AI)
algorithms capable of supporting advancement in cardiac clinical research. However …
algorithms capable of supporting advancement in cardiac clinical research. However …
An efficient dimensionality reduction based on adaptive-GSM and transformer assisted classification for high dimensional data
N Rajender, MV Gopalachari - International Journal of Information …, 2024 - Springer
Over the last decade, a surge in multimedia data has significantly impacted research areas
like multimedia retrieval, database management, and medical imaging. Traditional machine …
like multimedia retrieval, database management, and medical imaging. Traditional machine …
Hybrid Blended Deep Learning Approach for Milk Quality Analysis
RU Mhapsekar, N O'Shea, S Davy… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
There has been an increase in the implementation of Artificial Intelligence (AI) in the dairy
industry for Milk Quality Analysis (MQA). However, traditional Machine Learning (ML) …
industry for Milk Quality Analysis (MQA). However, traditional Machine Learning (ML) …
Deep-Learning-Based Arrhythmia Detection Using ECG Signals: A Comparative Study and Performance Evaluation
Heart diseases is the world's principal cause of death, and arrhythmia poses a serious risk to
the health of the patient. Electrocardiogram (ECG) signals can be used to detect arrhythmia …
the health of the patient. Electrocardiogram (ECG) signals can be used to detect arrhythmia …
ESOA-HGRU: egret swarm optimization algorithm-based hybrid gated recurrent unit for classification of diabetic retinopathy
AM Alajlan, A Razaque - Artificial Intelligence Review, 2023 - Springer
Diabetes is a chronic disease that affects people all over the world and raises the glucose
level in the blood as a result of a lack of insulin. Diabetic Retinopathy causes retinal eye …
level in the blood as a result of a lack of insulin. Diabetic Retinopathy causes retinal eye …
Harnessing the multimodal data integration and deep learning for occupational injury severity prediction
Most previous studies have neglected the potential of integrating structured data and
unstructured workplace injury reports to perform a predictive analysis of occupational injury …
unstructured workplace injury reports to perform a predictive analysis of occupational injury …
Optimization-enabled deep convolutional neural network with multiple features for cardiac arrhythmia classification using ECG signals
A Soman, R Sarath - Biomedical Signal Processing and Control, 2024 - Elsevier
Arrhythmia is a heart disorder because of irregular electrical activity of the heart. Generally,
an electrocardiogram (ECG) is a device used by a medical specialist to determine heart …
an electrocardiogram (ECG) is a device used by a medical specialist to determine heart …
An adaptive Marine Predator Optimization Algorithm (MPOA) integrated Gated Recurrent Neural Network (GRNN) classifier model for arrhythmia detection
R Pashikanti, CY Patil, SA Anirudhe - Biomedical Signal Processing and …, 2024 - Elsevier
Cardiovascular disorders are typically diagnosed using an Electrocardiogram (ECG). It is a
painless method that mimics the cyclical contraction and relaxation of the heart's muscles …
painless method that mimics the cyclical contraction and relaxation of the heart's muscles …