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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

RETRACTED ARTICLE: Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals
Paweł Pławiak, U. Rajendra Acharya
Neural Computing and Applications (2019) Vol. 32, Iss. 15, pp. 11137-11161
Open Access | Times Cited: 229

Showing 1-25 of 229 citing articles:

Classification of myocardial infarction with multi-lead ECG signals and deep CNN
Ulaş Baran Baloğlu, Muhammed Talo, Özal Yıldırım, et al.
Pattern Recognition Letters (2019) Vol. 122, pp. 23-30
Closed Access | Times Cited: 396
A new approach for arrhythmia classification using deep coded features and LSTM networks
Özal Yıldırım, Ulaş Baran Baloğlu, Ru San Tan, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 176, pp. 121-133
Closed Access | Times Cited: 316
A new machine learning technique for an accurate diagnosis of coronary artery disease
Moloud Abdar, Wojciech Książek, U. Rajendra Acharya, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 179, pp. 104992-104992
Closed Access | Times Cited: 291
Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review
Fatma Murat, Özal Yıldırım, Muhammed Talo, et al.
Computers in Biology and Medicine (2020) Vol. 120, pp. 103726-103726
Open Access | Times Cited: 266
Machine learning-based heart disease diagnosis: A systematic literature review
Md Manjurul Ahsan, Zahed Siddique
Artificial Intelligence in Medicine (2022) Vol. 128, pp. 102289-102289
Open Access | Times Cited: 261
Automated Depression Detection Using Deep Representation and Sequence Learning with EEG Signals
Betül Ay, Özal Yıldırım, Muhammed Talo, et al.
Journal of Medical Systems (2019) Vol. 43, Iss. 7
Closed Access | Times Cited: 238
Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals
Türker Tuncer, Şengül Doğan, Paweł Pławiak, et al.
Knowledge-Based Systems (2019) Vol. 186, pp. 104923-104923
Closed Access | Times Cited: 193
Generalization of Convolutional Neural Networks for ECG Classification Using Generative Adversarial Networks
Abdelrahman Shaker, Manal Tantawi, Howida A. Shedeed, et al.
IEEE Access (2020) Vol. 8, pp. 35592-35605
Open Access | Times Cited: 192
Comprehensive electrocardiographic diagnosis based on deep learning
Oh Shu Lih, Jahmunah Vicnesh, Ru San Tan, et al.
Artificial Intelligence in Medicine (2020) Vol. 103, pp. 101789-101789
Open Access | Times Cited: 190
Application of new deep genetic cascade ensemble of SVM classifiers to predict the Australian credit scoring
Paweł Pławiak, Moloud Abdar, U. Rajendra Acharya
Applied Soft Computing (2019) Vol. 84, pp. 105740-105740
Closed Access | Times Cited: 154
DepHNN: A novel hybrid neural network for electroencephalogram (EEG)-based screening of depression
Geetanjali Sharma, Abhishek Parashar, Amit M. Joshi
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102393-102393
Closed Access | Times Cited: 141
Prediction of heart disease and classifiers’ sensitivity analysis
Khaled Mohamad Almustafa
BMC Bioinformatics (2020) Vol. 21, Iss. 1
Open Access | Times Cited: 140
A Study on Arrhythmia via ECG Signal Classification Using the Convolutional Neural Network
Mengze Wu, Yongdi Lu, Wenli Yang, et al.
Frontiers in Computational Neuroscience (2021) Vol. 14
Open Access | Times Cited: 127
Hybrid CNN-LSTM deep learning model and ensemble technique for automatic detection of myocardial infarction using big ECG data
Hari Mohan, Kalyan Chatterjee
Applied Intelligence (2021) Vol. 52, Iss. 5, pp. 5366-5384
Closed Access | Times Cited: 121
Myocardial infarction detection based on deep neural network on imbalanced data
Mohamed Hammad, Monagi H. Alkinani, Brij B. Gupta, et al.
Multimedia Systems (2021) Vol. 28, Iss. 4, pp. 1373-1385
Closed Access | Times Cited: 118
Automated detection of coronary artery disease, myocardial infarction and congestive heart failure using GaborCNN model with ECG signals
V. Jahmunah, E. Y. K. Ng, Ru San Tan, et al.
Computers in Biology and Medicine (2021) Vol. 134, pp. 104457-104457
Closed Access | Times Cited: 106
An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices
Amadu Fullah Kamara, Enhong Chen, Zhen Pan
Information Sciences (2022) Vol. 594, pp. 1-19
Closed Access | Times Cited: 71
Electrocardiogram Monitoring Wearable Devices and Artificial-Intelligence-Enabled Diagnostic Capabilities: A Review
Luca Neri, Matt T. Oberdier, Kirsten C. J. van Abeelen, et al.
Sensors (2023) Vol. 23, Iss. 10, pp. 4805-4805
Open Access | Times Cited: 46
An improved method to detect arrhythmia using ensemble learning-based model in multi lead electrocardiogram (ECG)
Satria Mandala, Ardian Rizal, Adiwijaya Adiwijaya, et al.
PLoS ONE (2024) Vol. 19, Iss. 4, pp. e0297551-e0297551
Open Access | Times Cited: 18
A hierarchical method based on weighted extreme gradient boosting in ECG heartbeat classification
Haotian Shi, Haoren Wang, Yixiang Huang, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 171, pp. 1-10
Closed Access | Times Cited: 135
DGHNL: A new deep genetic hierarchical network of learners for prediction of credit scoring
Paweł Pławiak, Moloud Abdar, Joanna Pławiak, et al.
Information Sciences (2019) Vol. 516, pp. 401-418
Open Access | Times Cited: 135
An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset
Junli Gao, Hongpo Zhang, Peng Lu, et al.
Journal of Healthcare Engineering (2019) Vol. 2019, pp. 1-10
Open Access | Times Cited: 133
An ensemble learning approach for brain cancer detection exploiting radiomic features
Luca Brunese, Francesco Mercaldo, Alfonso Reginelli, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 185, pp. 105134-105134
Closed Access | Times Cited: 116
ResNet‐Attention model for human authentication using ECG signals
Mohamed Hammad, Paweł Pławiak, Kuanquan Wang, et al.
Expert Systems (2020) Vol. 38, Iss. 6
Closed Access | Times Cited: 116
Detection of myocardial infarction based on novel deep transfer learning methods for urban healthcare in smart cities
Ahmed S. Alghamdi, Mohamed Hammad, Hassan Ugail, et al.
Multimedia Tools and Applications (2020) Vol. 83, Iss. 5, pp. 14913-14934
Closed Access | Times Cited: 115
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