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OpenAlex Citation Counts

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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:

ECG arrhythmia classification based on optimum-path forest
Eduardo Luz, Thiago Nunes, Victor Hugo C. de Albuquerque, et al.
Expert Systems with Applications (2012) Vol. 40, Iss. 9, pp. 3561-3573
Open Access | Times Cited: 168

Showing 1-25 of 168 citing articles:

ECG-based heartbeat classification for arrhythmia detection: A survey
Eduardo Luz, William Robson Schwartz, Guillermo Cámara-Chávez, et al.
Computer Methods and Programs in Biomedicine (2015) Vol. 127, pp. 144-164
Open Access | Times Cited: 782
Arrhythmia detection using deep convolutional neural network with long duration ECG signals
Özal Yıldırım, Paweł Pławiak, Ru San Tan, et al.
Computers in Biology and Medicine (2018) Vol. 102, pp. 411-420
Closed Access | Times Cited: 716
Deep learning approach for active classification of electrocardiogram signals
Mohamad Mahmoud Al Rahhal, Yakoub Bazi, Haikel Alhichri, et al.
Information Sciences (2016) Vol. 345, pp. 340-354
Open Access | Times Cited: 587
A survey on ECG analysis
Selcan Kaplan Berkaya, Alper Kürşat Uysal, Efnan Şora Günal, et al.
Biomedical Signal Processing and Control (2018) Vol. 43, pp. 216-235
Closed Access | Times Cited: 442
ECG Classification Using Wavelet Packet Entropy and Random Forests
Taiyong Li, Min Zhou
Entropy (2016) Vol. 18, Iss. 8, pp. 285-285
Open Access | Times Cited: 436
Machine-Learning-Based Disease Diagnosis: A Comprehensive Review
Md Manjurul Ahsan, Shahana Akter Luna, Zahed Siddique
Healthcare (2022) Vol. 10, Iss. 3, pp. 541-541
Open Access | Times Cited: 310
Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers
Víctor Manuel Mondéjar-Guerra, Jorge Novo, José Rouco, et al.
Biomedical Signal Processing and Control (2018) Vol. 47, pp. 41-48
Open Access | Times Cited: 257
Advances in Photopletysmography Signal Analysis for Biomedical Applications
Jermana Lopes de Moraes, Matheus Lavorenti Rocha, Glauber Gean de Vasconcelos, et al.
Sensors (2018) Vol. 18, Iss. 6, pp. 1894-1894
Open Access | Times Cited: 252
Novel methodology of cardiac health recognition based on ECG signals and evolutionary-neural system
Paweł Pławiak
Expert Systems with Applications (2017) Vol. 92, pp. 334-349
Open Access | Times Cited: 239
Classification of ECG Arrhythmia using Recurrent Neural Networks
Shraddha Singh, Saroj Kumar Pandey, Urja Pawar, et al.
Procedia Computer Science (2018) Vol. 132, pp. 1290-1297
Open Access | Times Cited: 230
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
Multiresolution wavelet transform based feature extraction and ECG classification to detect cardiac abnormalities
Santanu Sahoo, Bhupen Kanungo, Suresh Kumar Behera, et al.
Measurement (2017) Vol. 108, pp. 55-66
Closed Access | Times Cited: 227
Automatic 3D pulmonary nodule detection in CT images: A survey
Igor Rafael S. Valente, Paulo César Cortez, Edson Cavalcanti Neto, et al.
Computer Methods and Programs in Biomedicine (2015) Vol. 124, pp. 91-107
Open Access | Times Cited: 215
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: 126
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
Novel genetic ensembles of classifiers applied to myocardium dysfunction recognition based on ECG signals
Paweł Pławiak
Swarm and Evolutionary Computation (2017) Vol. 39, pp. 192-208
Open Access | Times Cited: 146
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: 134
Semi-supervised Stacked Label Consistent Autoencoder for Reconstruction and Analysis of Biomedical Signals
Anupriya Gogna, Angshul Majumdar, Rabab Ward
IEEE Transactions on Biomedical Engineering (2016) Vol. 64, Iss. 9, pp. 2196-2205
Open Access | Times Cited: 133
A novel electrocardiogram feature extraction approach for cardiac arrhythmia classification
Leandro B. Marinho, Navar Medeiros M. Nascimento, João Wellington M. Souza, et al.
Future Generation Computer Systems (2019) Vol. 97, pp. 564-577
Closed Access | Times Cited: 130
DENS-ECG: A deep learning approach for ECG signal delineation
Abdolrahman Peimankar, Sadasivan Puthusserypady
Expert Systems with Applications (2020) Vol. 165, pp. 113911-113911
Open Access | Times Cited: 125
Sparse representation of ECG signals for automated recognition of cardiac arrhythmias
Sandeep Raj, Kailash Chandra Ray
Expert Systems with Applications (2018) Vol. 105, pp. 49-64
Closed Access | Times Cited: 122
An Automatic Cardiac Arrhythmia Classification System With Wearable Electrocardiogram
Yufa Xia, Huailing Zhang, Lin Xu, et al.
IEEE Access (2018) Vol. 6, pp. 16529-16538
Open Access | Times Cited: 115
A global and updatable ECG beat classification system based on recurrent neural networks and active learning
Guijin Wang, Chenshuang Zhang, Yongpan Liu, et al.
Information Sciences (2018) Vol. 501, pp. 523-542
Closed Access | Times Cited: 108
EEG signal classification for epilepsy diagnosis via optimum path forest – A systematic assessment
Thiago Nunes, André L. V. Coelho, Clodoaldo A. M. Lima, et al.
Neurocomputing (2014) Vol. 136, pp. 103-123
Closed Access | Times Cited: 98
A Review on the State of the Art in Atrial Fibrillation Detection Enabled by Machine Learning
Ali Rizwan, Ahmed Zoha, Ismail Ben Mabrouk, et al.
IEEE Reviews in Biomedical Engineering (2020) Vol. 14, pp. 219-239
Open Access | Times Cited: 89
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