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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:

A Multi-view Deep Learning Method for Epileptic Seizure Detection using Short-time Fourier Transform
Ye Yuan, Guangxu Xun, Kebin Jia, et al.
(2017), pp. 213-222
Closed Access | Times Cited: 100

Showing 1-25 of 100 citing articles:

Epileptic Seizures Detection Using Deep Learning Techniques: A Review
Afshin Shoeibi, Marjane Khodatars, Navid Ghassemi, et al.
International Journal of Environmental Research and Public Health (2021) Vol. 18, Iss. 11, pp. 5780-5780
Open Access | Times Cited: 306
A review of feature extraction and performance evaluation in epileptic seizure detection using EEG
Poomipat Boonyakitanont, Apiwat Lek-uthai, Krisnachai Chomtho, et al.
Biomedical Signal Processing and Control (2019) Vol. 57, pp. 101702-101702
Open Access | Times Cited: 293
A Multi-View Deep Learning Framework for EEG Seizure Detection
Ye Yuan, Guangxu Xun, Kebin Jia, et al.
IEEE Journal of Biomedical and Health Informatics (2018) Vol. 23, Iss. 1, pp. 83-94
Closed Access | Times Cited: 217
Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals
Ramy Hussein, Hamid Palangi, Rabab Ward, et al.
Clinical Neurophysiology (2018) Vol. 130, Iss. 1, pp. 25-37
Closed Access | Times Cited: 214
Epileptic Seizures Prediction Using Deep Learning Techniques
Syed Muhammad Usman, Shehzad Khalid, Muhammad Haseeb Aslam
IEEE Access (2020) Vol. 8, pp. 39998-40007
Open Access | Times Cited: 167
A Deep Learning Approach for Automatic Seizure Detection in Children With Epilepsy
Ahmed Abdelhameed, Magdy Bayoumi
Frontiers in Computational Neuroscience (2021) Vol. 15
Open Access | Times Cited: 133
EEG seizure detection: concepts, techniques, challenges, and future trends
Athar A. Ein Shoka, Mohamed M. Dessouky, Ayman El‐Sayed, et al.
Multimedia Tools and Applications (2023) Vol. 82, Iss. 27, pp. 42021-42051
Open Access | Times Cited: 52
Auto-detection of epileptic seizure events using deep neural network with different feature scaling techniques
D. K. Thara, B. G. Premasudha, Fan Xiong
Pattern Recognition Letters (2019) Vol. 128, pp. 544-550
Closed Access | Times Cited: 141
Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders
U. Raghavendra, U. Rajendra Acharya, Hojjat Adeli
European Neurology (2019) Vol. 82, Iss. 1-3, pp. 41-64
Open Access | Times Cited: 132
Deep Patient Similarity Learning for Personalized Healthcare
Qiuling Suo, Fenglong Ma, Ye Yuan, et al.
IEEE Transactions on NanoBioscience (2018) Vol. 17, Iss. 3, pp. 219-227
Open Access | Times Cited: 124
Automatic Seizure Detection using Fully Convolutional Nested LSTM
Yang Li, Zuyi Yu, Yang Chen, et al.
International Journal of Neural Systems (2020) Vol. 30, Iss. 04, pp. 2050019-2050019
Closed Access | Times Cited: 111
Personalized disease prediction using a CNN-based similarity learning method
Qiuling Suo, Fenglong Ma, Ye Yuan, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2017)
Closed Access | Times Cited: 88
Epileptic Signal Classification With Deep EEG Features by Stacked CNNs
Jiuwen Cao, Jiahua Zhu, Wenbin Hu, et al.
IEEE Transactions on Cognitive and Developmental Systems (2019) Vol. 12, Iss. 4, pp. 709-722
Closed Access | Times Cited: 87
One dimensional convolutional neural networks for seizure onset detection using long-term scalp and intracranial EEG
Xiaoshuang Wang, Xiulin Wang, Wenya Liu, et al.
Neurocomputing (2021) Vol. 459, pp. 212-222
Open Access | Times Cited: 86
Epileptic Seizure Prediction With Multi-View Convolutional Neural Networks
Chien‐Liang Liu, Bin Xiao, Wen-Hoar Hsaio, et al.
IEEE Access (2019) Vol. 7, pp. 170352-170361
Open Access | Times Cited: 82
A Recent Investigation on Detection and Classification of Epileptic Seizure Techniques Using EEG Signal
Sani Saminu, Guizhi Xu, Shuai Zhang, et al.
Brain Sciences (2021) Vol. 11, Iss. 5, pp. 668-668
Open Access | Times Cited: 66
An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works
Afshin Shoeibi, Parisa Moridian, Marjane Khodatars, et al.
Computers in Biology and Medicine (2022) Vol. 149, pp. 106053-106053
Open Access | Times Cited: 58
Applications of Artificial Intelligence in Automatic Detection of Epileptic Seizures Using EEG Signals: A Review
Sani Saminu, Guizhi Xu, Shuai Zhang, et al.
Artificial Intelligence and Applications (2022) Vol. 1, Iss. 1, pp. 11-25
Open Access | Times Cited: 41
Epileptic Seizure Detection Using Machine Learning: Taxonomy, Opportunities, and Challenges
Muhammad Shoaib Farooq, Aimen Zulfiqar, Shamyla Riaz
Diagnostics (2023) Vol. 13, Iss. 6, pp. 1058-1058
Open Access | Times Cited: 35
Epileptic Seizure Detection and Prediction in EEGs Using Power Spectra Density Parameterization
Shan Liu, Jiang Wang, Shanshan Li, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2023) Vol. 31, pp. 3884-3894
Open Access | Times Cited: 25
Epileptic seizure detection and prediction using stacked bidirectional long short term memory
D. K. Thara, B. G. Premasudha, Fan Xiong
Pattern Recognition Letters (2019) Vol. 128, pp. 529-535
Closed Access | Times Cited: 75
A novel channel-aware attention framework for multi-channel EEG seizure detection via multi-view deep learning
Ye Yuan, Guangxu Xun, Fenglong Ma, et al.
(2018), pp. 206-209
Closed Access | Times Cited: 66
Spectrum Analysis of EEG Signals Using CNN to Model Patient’s Consciousness Level Based on Anesthesiologists’ Experience
Quan Liu, Jifa Cai, Shou‐Zen Fan, et al.
IEEE Access (2019) Vol. 7, pp. 53731-53742
Open Access | Times Cited: 64
MuVAN: A Multi-view Attention Network for Multivariate Temporal Data
Ye Yuan, Guangxu Xun, Fenglong Ma, et al.
2021 IEEE International Conference on Data Mining (ICDM) (2018), pp. 717-726
Closed Access | Times Cited: 62
Change Point Detection in Time Series Data Using Autoencoders With a Time-Invariant Representation
Tim De Ryck, Maarten De Vos, Alexander Bertrand
IEEE Transactions on Signal Processing (2021) Vol. 69, pp. 3513-3524
Open Access | Times Cited: 53
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