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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 Deep Learning Approach for Mild Depression Recognition Based on Functional Connectivity Using Electroencephalography
Xiaowei Li, Rong La, Ying Wang, et al.
Frontiers in Neuroscience (2020) Vol. 14
Open Access | Times Cited: 94

Showing 1-25 of 94 citing articles:

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
Natural and Artificial Intelligence: A brief introduction to the interplay between AI and neuroscience research
Tom Macpherson, Anne K. Churchland, Terry Sejnowski, et al.
Neural Networks (2021) Vol. 144, pp. 603-613
Open Access | Times Cited: 102
Machine Learning Algorithms for Depression: Diagnosis, Insights, and Research Directions
Shumaila Aleem, Noor ul Huda, Rashid Amin, et al.
Electronics (2022) Vol. 11, Iss. 7, pp. 1111-1111
Open Access | Times Cited: 82
Depression Detection From Social Networks Data Based on Machine Learning and Deep Learning Techniques: An Interrogative Survey
Khan Md. Hasib, Md Rafiqul Islam, Shadman Sakib, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 10, Iss. 4, pp. 1568-1586
Closed Access | Times Cited: 57
The applied principles of EEG analysis methods in neuroscience and clinical neurology
Hao Zhang, Qing-Qi Zhou, He Chen, et al.
Military Medical Research (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 44
Unravelling the complexities of depression with medical intelligence: exploring the interplay of genetics, hormones, and brain function
Md Belal Bin Heyat, Faijan Akhtar, Farwa Munir, et al.
Complex & Intelligent Systems (2024) Vol. 10, Iss. 4, pp. 5883-5915
Open Access | Times Cited: 19
Brain Functional Networks Based on Resting-State EEG Data for Major Depressive Disorder Analysis and Classification
Bingtao Zhang, Guanghui Yan, Zhifei Yang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2020) Vol. 29, pp. 215-229
Open Access | Times Cited: 83
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
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 Diagnosis of Major Depressive Disorder Using Brain Effective Connectivity and 3D Convolutional Neural Network
Danish M. Khan, Norashikin Yahya, Nidal Kamel, et al.
IEEE Access (2021) Vol. 9, pp. 8835-8846
Open Access | Times Cited: 55
A Clinical-Oriented Non-Severe Depression Diagnosis Method Based on Cognitive Behavior of Emotional Conflict
Mi Li, Jinyu Zhang, Jie Song, et al.
IEEE Transactions on Computational Social Systems (2022) Vol. 10, Iss. 1, pp. 131-141
Closed Access | Times Cited: 52
EEG based depression recognition using improved graph convolutional neural network
Jing Zhu, Changting Jiang, Junhao Chen, et al.
Computers in Biology and Medicine (2022) Vol. 148, pp. 105815-105815
Closed Access | Times Cited: 45
EEG-Based Graph Neural Network Classification of Alzheimer’s Disease: An Empirical Evaluation of Functional Connectivity Methods
Dominik Klepl, Fei He, Min Wu, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022) Vol. 30, pp. 2651-2660
Open Access | Times Cited: 40
Machine learning based approaches for clinical and non-clinical depression recognition and depression relapse prediction using audiovisual and EEG modalities: A comprehensive review
Sana Yasin, Alice Othmani, Imran Raza, et al.
Computers in Biology and Medicine (2023) Vol. 159, pp. 106741-106741
Closed Access | Times Cited: 30
TSF-MDD: A Deep Learning Approach for Electroencephalography-Based Diagnosis of Major Depressive Disorder with Temporal–Spatial–Frequency Feature Fusion
Wei Gan, R. P. Zhao, Yujie Ma, et al.
Bioengineering (2025) Vol. 12, Iss. 2, pp. 95-95
Open Access | Times Cited: 1
Intelligent Internet of Medical Things for Depression: Current Advancements, Challenges, and Trends
Md Belal Bin Heyat, Deepak Adhikari, Faijan Akhtar, et al.
International Journal of Intelligent Systems (2025) Vol. 2025, Iss. 1
Open Access | Times Cited: 1
Automated diagnosis of depression from EEG signals using traditional and deep learning approaches: A comparative analysis
Ashima Khosla, Padmavati Khandnor, Trilok Chand
Journal of Applied Biomedicine (2021) Vol. 42, Iss. 1, pp. 108-142
Closed Access | Times Cited: 51
Deep learning applied to electroencephalogram data in mental disorders: A systematic review
Mateo de Bardeci, Cheng-Teng Ip, Sebastian Olbrich
Biological Psychology (2021) Vol. 162, pp. 108117-108117
Open Access | Times Cited: 49
Depression Analysis and Recognition Based on Functional Near-Infrared Spectroscopy
Rui Wang, Yixue Hao, Yu Qiao, et al.
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 25, Iss. 12, pp. 4289-4299
Closed Access | Times Cited: 46
EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review
Sara Ballanti, Silvia Campagnini, Piergiuseppe Liuzzi, et al.
Clinical Neurophysiology (2022) Vol. 144, pp. 98-114
Open Access | Times Cited: 28
An End-to-End Deep Learning Model for EEG-Based Major Depressive Disorder Classification
Min Xia, Yangsong Zhang, Yihan Wu, et al.
IEEE Access (2023) Vol. 11, pp. 41337-41347
Open Access | Times Cited: 18
Data leakage in deep learning studies of translational EEG
Geoffrey Brookshire, Jake Kasper, Nicholas M. Blauch, et al.
Frontiers in Neuroscience (2024) Vol. 18
Open Access | Times Cited: 7
Deep-Asymmetry: Asymmetry Matrix Image for Deep Learning Method in Pre-Screening Depression
Min Kang, Hyunjin Kwon, Jinhyeok Park, et al.
Sensors (2020) Vol. 20, Iss. 22, pp. 6526-6526
Open Access | Times Cited: 45
GNN-Based Depression Recognition Using Spatio-Temporal Information: A fNIRS Study
Yu Qiao, Rui Wang, Jia Liu, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 10, pp. 4925-4935
Closed Access | Times Cited: 25
EEG-based classification of individuals with neuropsychiatric disorders using deep neural networks: A systematic review of current status and future directions
Mohsen Parsa, Habib Yousefi Rad, Hadi Vaezi, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 240, pp. 107683-107683
Closed Access | Times Cited: 15
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