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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:

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: 74

Showing 1-25 of 74 citing articles:

The Personal Health Applications of Machine Learning Techniques in the Internet of Behaviors
Zahra Mohtasham‐Amiri, Arash Heidari, Mehdi Darbandi, et al.
Sustainability (2023) Vol. 15, Iss. 16, pp. 12406-12406
Open Access | Times Cited: 58
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: 56
Depression Sentiment Analysis using Machine Learning Techniques:A Review
Ashwani Kumar, Sunita Beniwal
International Journal of Computational and Experimental Science and Engineering (2025) Vol. 11, Iss. 1
Open Access | Times Cited: 2
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: 57
DepCap: A Smart Healthcare Framework for EEG Based Depression Detection Using Time-Frequency Response and Deep Neural Network
Geetanjali Sharma, Amit M. Joshi, Richa Gupta, et al.
IEEE Access (2023) Vol. 11, pp. 52327-52338
Open Access | Times Cited: 27
Time frequency images as predictors for depressed patients’ respondent status to SSRI antidepressant
Wael Korani, Shyam Sundar Domakonda
Biomedical Signal Processing and Control (2025) Vol. 104, pp. 107440-107440
Closed Access | Times Cited: 1
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 | Times Cited: 1
OSACN-Net: Automated Classification of Sleep Apnea Using Deep Learning Model and Smoothed Gabor Spectrograms of ECG Signal
Kapil Gupta, Varun Bajaj, Irshad Ahmad Ansari
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 71, pp. 1-9
Closed Access | Times Cited: 46
Automated Detection of Major Depressive Disorder With EEG Signals: A Time Series Classification Using Deep Learning
Alireza Rafiei, Rasoul Zahedifar, Chiranjibi Sitaula, et al.
IEEE Access (2022) Vol. 10, pp. 73804-73817
Open Access | Times Cited: 34
Deep learning in neuroimaging data analysis: Applications, challenges, and solutions
Lev Kiar Avberšek, Grega Repovš
Frontiers in Neuroimaging (2022) Vol. 1
Open Access | Times Cited: 29
Novel Mixed Domain Hand-Crafted Features for Skin Disease Recognition Using Multiheaded CNN
Anurodh Kumar, Amit Vishwakarma, Varun Bajaj, et al.
IEEE Transactions on Instrumentation and Measurement (2024) Vol. 73, pp. 1-13
Closed Access | Times Cited: 8
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: 16
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
Estimating the Depth of Anesthesia from EEG Signals Based on a Deep Residual Shrinkage Network
Meng Shi, Ziyu Huang, Guowen Xiao, et al.
Sensors (2023) Vol. 23, Iss. 2, pp. 1008-1008
Open Access | Times Cited: 14
A Framework for Systematically Evaluating the Representations Learned by A Deep Learning Classifier from Raw Multi-Channel Electroencephalogram Data
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 13
A novel ternary pattern-based automatic psychiatric disorders classification using ECG signals
Burak Taşçı, Gülay TAŞCI, Şengül Doğan, et al.
Cognitive Neurodynamics (2022) Vol. 18, Iss. 1, pp. 95-108
Closed Access | Times Cited: 21
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
Development of Artificial Intelligence for Determining Major Depressive Disorder Based on Resting-State EEG and Single-Pulse Transcranial Magnetic Stimulation-Evoked EEG Indices
Yoshihiro Noda, Kento Sakaue, Masataka Wada, et al.
Journal of Personalized Medicine (2024) Vol. 14, Iss. 1, pp. 101-101
Open Access | Times Cited: 4
Transformer-based fusion model for mild depression recognition with EEG and pupil area signals
Jing Zhu, Yuanlong Li, Changlin Yang, et al.
Medical & Biological Engineering & Computing (2025)
Closed Access
A Survey of Current Progress in Depression Detection Using Deep Learning and Machine Learning
Meena Kumari, Gurpreet Singh, Sagar Dhanraj Pande
Deleted Journal (2025)
Closed Access
WIVIDOSA-Net: Wigner-Ville distribution based obstructive sleep apnea detection using single lead ECG signal
Amit Bhongade, Tapan Kumar Gandhi
Biomedical Engineering Advances (2025), pp. 100159-100159
Open Access
Detection of event-related potentials as a biomarker in major depressive disorder using an XGBoost model
Yuhang Pan, Jing Jie, Ming Yin
Biomedical Signal Processing and Control (2025) Vol. 108, pp. 107879-107879
Closed Access
Applying the parametric learning tactic along with the Welch signal processing technique in designing a depression recognition system using electroencephalogram
Melika Changizi, Saeid Rashidi, Mahdi Zolfagharzadeh-Kermani
Biomedical Signal Processing and Control (2025) Vol. 108, pp. 107921-107921
Closed Access
Spatial–Temporal EEG Fusion Based on Neural Network for Major Depressive Disorder Detection
Bingtao Zhang, Dan Wei, Guanghui Yan, et al.
Interdisciplinary Sciences Computational Life Sciences (2023) Vol. 15, Iss. 4, pp. 542-559
Open Access | Times Cited: 10
Artificial intelligence empowering research on loneliness, depression and anxiety — Using Covid-19 as an opportunity
Qijian Zheng, Feng Liu, Shuya Xu, et al.
Journal of Safety Science and Resilience (2023) Vol. 4, Iss. 4, pp. 396-409
Open Access | Times Cited: 9
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