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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:

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

Showing 1-25 of 238 citing articles:

DeprNet: A Deep Convolution Neural Network Framework for Detecting Depression Using EEG
Ayan Seal, Rishabh Bajpai, Jagriti Agnihotri, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-13
Closed Access | Times Cited: 161
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks:A review
Sana Yasin, Syed Asad Hussain, Sinem Aslan, et al.
Computer Methods and Programs in Biomedicine (2021) Vol. 202, pp. 106007-106007
Open 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
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
MS-MDA: Multisource Marginal Distribution Adaptation for Cross-Subject and Cross-Session EEG Emotion Recognition
Hao Chen, Ming Jin, Zhunan Li, et al.
Frontiers in Neuroscience (2021) Vol. 15
Open Access | Times Cited: 105
Artificial intelligence and Psychiatry: An overview
Adwitiya Ray, Akansha Bhardwaj, Yogender Kumar Malik, et al.
Asian Journal of Psychiatry (2022) Vol. 70, pp. 103021-103021
Open Access | Times Cited: 78
Modern Methods of Diagnostics and Treatment of Neurodegenerative Diseases and Depression
Natalia Shusharina, Denis Yukhnenko, Stepan Botman, et al.
Diagnostics (2023) Vol. 13, Iss. 3, pp. 573-573
Open Access | Times Cited: 55
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: 131
A deep learning framework for automatic diagnosis of unipolar depression
Wajid Mumtaz, Abdul Qayyum
International Journal of Medical Informatics (2019) Vol. 132, pp. 103983-103983
Closed Access | Times Cited: 129
Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach
Abdolkarim Saeedi, Maryam Saeedi, Arash Maghsoudi, et al.
Cognitive Neurodynamics (2020) Vol. 15, Iss. 2, pp. 239-252
Open Access | Times Cited: 126
Accurate deep neural network model to detect cardiac arrhythmia on more than 10,000 individual subject ECG records
Özal Yıldırım, Muhammed Talo, Edward J. Ciaccio, et al.
Computer Methods and Programs in Biomedicine (2020) Vol. 197, pp. 105740-105740
Open Access | Times Cited: 103
A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis
Reza Akbari Movahed, Gila Pirzad Jahromi, Shima Shahyad, et al.
Journal of Neuroscience Methods (2021) Vol. 358, pp. 109209-109209
Closed Access | Times Cited: 99
Enhancing EEG-Based Classification of Depression Patients Using Spatial Information
Chao Jiang, Yingjie Li, Yingying Tang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2021) Vol. 29, pp. 566-575
Open Access | Times Cited: 79
An Improved Classification Model for Depression Detection Using EEG and Eye Tracking Data
Jing Zhu, Zihan Wang, Tao Gong, et al.
IEEE Transactions on NanoBioscience (2020) Vol. 19, Iss. 3, pp. 527-537
Closed Access | Times Cited: 72
Deep Learning in EEG: Advance of the Last Ten-Year Critical Period
Shu Gong, Kaibo Xing, Andrzej Cichocki, et al.
IEEE Transactions on Cognitive and Developmental Systems (2021) Vol. 14, Iss. 2, pp. 348-365
Open Access | Times Cited: 72
Decision support system for major depression detection using spectrogram and convolution neural network with EEG signals
Hui Wen Loh, Chui Ping Ooi, Emrah Aydemir, et al.
Expert Systems (2021) Vol. 39, Iss. 3
Closed Access | Times Cited: 72
Diagnosis and prognosis of mental disorders by means of EEG and deep learning: a systematic mapping study
Manuel J. Rivera, Miguel A. Teruel, Alejandro Maté, et al.
Artificial Intelligence Review (2021) Vol. 55, Iss. 2, pp. 1209-1251
Closed Access | Times Cited: 64
A deep learning-based comparative study to track mental depression from EEG data
Avik Sarkar, Ankita Singh, Rakhi Chakraborty
Neuroscience Informatics (2022) Vol. 2, Iss. 4, pp. 100039-100039
Closed Access | Times Cited: 61
Exploration of EEG-Based Depression Biomarkers Identification Techniques and Their Applications: A Systematic Review
Antora Dev, N. Roy, Md. Kafiul Islam, et al.
IEEE Access (2022) Vol. 10, pp. 16756-16781
Open Access | Times Cited: 56
Automated accurate detection of depression using twin Pascal’s triangles lattice pattern with EEG Signals
Gülay TAŞCI, Hui Wen Loh, Prabal Datta Barua, et al.
Knowledge-Based Systems (2022) Vol. 260, pp. 110190-110190
Closed Access | Times Cited: 56
Prediction of drug response in major depressive disorder using ensemble of transfer learning with convolutional neural network based on EEG
Mohsen Sadat Shahabi, Ahmad Shalbaf, Arash Maghsoudi
Journal of Applied Biomedicine (2021) Vol. 41, Iss. 3, pp. 946-959
Closed Access | Times Cited: 55
Depression diagnosis by deep learning using EEG signals: A systematic review
Atefeh Safayari, Hamidreza Bolhasani
Medicine in Novel Technology and Devices (2021) Vol. 12, pp. 100102-100102
Open Access | Times Cited: 55
Deep learning techniques for suicide and depression detection from online social media: A scoping review
Anshu Malhotra, Rajni Jindal
Applied Soft Computing (2022) Vol. 130, pp. 109713-109713
Closed Access | Times Cited: 47
Exploring Self-Attention Graph Pooling With EEG-Based Topological Structure and Soft Label for Depression Detection
Tao Chen, Yanrong Guo, Shijie Hao, et al.
IEEE Transactions on Affective Computing (2022) Vol. 13, Iss. 4, pp. 2106-2118
Closed Access | Times Cited: 39
Electroencephalography-Based Depression Detection Using Multiple Machine Learning Techniques
Amel Ksibi, Mohammed Zakariah, Leila Jamel, et al.
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1779-1779
Open Access | Times Cited: 32
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