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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:

EEG-based mild depression recognition using convolutional neural network
Xiaowei Li, Rong La, Ying Wang, et al.
Medical & Biological Engineering & Computing (2019) Vol. 57, Iss. 6, pp. 1341-1352
Closed Access | Times Cited: 107

Showing 26-50 of 107 citing articles:

Continuous Scoring of Depression From EEG Signals via a Hybrid of Convolutional Neural Networks
Sara Hashempour, Reza Boostani, Mokhtar Mohammadi, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022) Vol. 30, pp. 176-183
Open Access | Times Cited: 35
EEG-based major depressive disorder recognition by selecting discriminative features via stochastic search
Hongli Chang, Yuan Zong, Wenming Zheng, et al.
Journal of Neural Engineering (2023) Vol. 20, Iss. 2, pp. 026021-026021
Closed Access | Times Cited: 19
High-Density Electroencephalography and Speech Signal Based Deep Framework for Clinical Depression Diagnosis
Abdul Qayyum, Imran Razzak, M. Tanveer, et al.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2023) Vol. 20, Iss. 4, pp. 2587-2597
Closed Access | Times Cited: 19
QLBP: Dynamic patterns-based feature extraction functions for automatic detection of mental health and cognitive conditions using EEG signals
Gülay TAŞCI, Mehmet Veysel Gün, Tuğçe Keleş, et al.
Chaos Solitons & Fractals (2023) Vol. 172, pp. 113472-113472
Closed Access | Times Cited: 19
A novel EEG-based graph convolution network for depression detection: Incorporating secondary subject partitioning and attention mechanism
Zhongyi Zhang, Qing‐Hao Meng, Li-Cheng Jin, et al.
Expert Systems with Applications (2023) Vol. 239, pp. 122356-122356
Closed Access | Times Cited: 19
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
Transfer learning for informative-frame selection in laryngoscopic videos through learned features
Ilaria Patrini, Michela Ruperti, Sara Moccia, et al.
Medical & Biological Engineering & Computing (2020) Vol. 58, Iss. 6, pp. 1225-1238
Open Access | Times Cited: 42
Depression signal correlation identification from different EEG channels based on CNN feature extraction
Baiyang Wang, Yuyun Kang, Dongyue Huo, et al.
Psychiatry Research Neuroimaging (2022) Vol. 328, pp. 111582-111582
Closed Access | Times Cited: 24
Depression screening using hybrid neural network
Jiao Zhang, Baomin Xu, Hongfeng Yin
Multimedia Tools and Applications (2023) Vol. 82, Iss. 17, pp. 26955-26970
Open Access | Times Cited: 15
DCTNet: hybrid deep neural network-based EEG signal for detecting depression
Yu Chen, Sheng Wang, Jifeng Guo
Multimedia Tools and Applications (2023) Vol. 82, Iss. 26, pp. 41307-41321
Closed Access | Times Cited: 15
Early detection of neurological abnormalities using a combined phase space reconstruction and deep learning approach
Amjed Al Fahoum, Ala’a Zyout
Intelligence-Based Medicine (2023) Vol. 8, pp. 100123-100123
Open Access | Times Cited: 15
EEG-based investigation of effects of mindfulness meditation training on state and trait by deep learning and traditional machine learning
Baoxiang Shang, Feiyan Duan, Ruiqi Fu, et al.
Frontiers in Human Neuroscience (2023) Vol. 17
Open Access | Times Cited: 14
Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI)
Min Hui Tan, Jinjin Zhao, Y. Tao, et al.
BMC Psychiatry (2025) Vol. 25, Iss. 1
Open Access
Computer-Aided Recognition Based on Decision-Level Multimodal Fusion for Depression
Bingtao Zhang, Hanshu Cai, Yubo Song, et al.
IEEE Journal of Biomedical and Health Informatics (2022) Vol. 26, Iss. 7, pp. 3466-3477
Closed Access | Times Cited: 21
Automatic feature learning model combining functional connectivity network and graph regularization for depression detection
Lijun Yang, Xiaoge Wei, Fengrui Liu, et al.
Biomedical Signal Processing and Control (2022) Vol. 82, pp. 104520-104520
Closed Access | Times Cited: 20
Machine Learning in ADHD and Depression Mental Health Diagnosis: A Survey
Christian Nash, Rajesh Nair, Syed Mohsen Naqvi
IEEE Access (2023) Vol. 11, pp. 86297-86317
Open Access | Times Cited: 12
Opportunities and Challenges for Clinical Practice in Detecting Depression Using EEG and Machine Learning
Damir Mulc, Jakša Vukojević, Eda Jovičić, et al.
Sensors (2025) Vol. 25, Iss. 2, pp. 409-409
Open Access
Depression Detection and Diagnosis Based on Electroencephalogram (EEG) Analysis: A Systematic Review
Kholoud Elnaggar, M. M. El-Gayar, Mohammed Elmogy
Diagnostics (2025) Vol. 15, Iss. 2, pp. 210-210
Open Access
MDD-SSTNet: detecting major depressive disorder by exploring spectral-spatial-temporal information on resting-state electroencephalography data based on deep neural network
Qiurong Chen, Min Xia, J Li, et al.
Cerebral Cortex (2025)
Closed Access
Research on Depression Recognition of EEG Signals Based on Spatio-Temporal Graph Convolutional Neural Network
静雯 石
Advances in Applied Mathematics (2025) Vol. 14, Iss. 02, pp. 14-24
Closed Access
A neural approach to the Turing Test: The role of emotions
Rita Pizzi, Hao Quan, Matteo Matteucci, et al.
Neural Networks (2025), pp. 107362-107362
Open Access
EEG-based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and their Applications
Xiaotong Gu, Zehong Cao, Alireza Jolfaei, et al.
arXiv (Cornell University) (2020)
Closed Access | Times Cited: 32
Multi-Head Attention-Based Long Short-Term Memory for Depression Detection From Speech
Yan Zhao, Zhenlin Liang, Jing Du, et al.
Frontiers in Neurorobotics (2021) Vol. 15
Open Access | Times Cited: 26
Prediction of depressive symptoms onset and long-term trajectories in home-based older adults using machine learning techniques
Shaowu Lin, Yafei Wu, Lingxiao He, et al.
Aging & Mental Health (2022) Vol. 27, Iss. 1, pp. 8-17
Closed Access | Times Cited: 18
Automated classification of multi-class sleep stages classification using polysomnography signals: a nine- layer 1D-convolution neural network approach
Santosh Kumar Satapathy, D. Loganathan
Multimedia Tools and Applications (2022) Vol. 82, Iss. 6, pp. 8049-8091
Closed Access | Times Cited: 18

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