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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:

Detection of major depressive disorder using linear and non-linear features from EEG signals
Shalini Mahato, Sanchita Paul
Microsystem Technologies (2018) Vol. 25, Iss. 3, pp. 1065-1076
Closed Access | Times Cited: 104

Showing 1-25 of 104 citing articles:

A Review on Mental Stress Detection Using Wearable Sensors and Machine Learning Techniques
Shruti Gedam, Sanchita Paul
IEEE Access (2021) Vol. 9, pp. 84045-84066
Open Access | Times Cited: 263
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: 156
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
Classification of Depression Patients and Normal Subjects Based on Electroencephalogram (EEG) Signal Using Alpha Power and Theta Asymmetry
Shalini Mahato, Sanchita Paul
Journal of Medical Systems (2019) Vol. 44, Iss. 1
Closed Access | Times Cited: 109
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: 100
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: 73
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
Detection of Depression and Scaling of Severity Using Six Channel EEG Data
Shalini Mahato, Nishant Goyal, Daya Ram, et al.
Journal of Medical Systems (2020) Vol. 44, Iss. 7
Closed Access | Times Cited: 70
Ensemble Approach for Detection of Depression Using EEG Features
Egils Avots, Klāvs Jermakovs, Maie Bachmann, et al.
Entropy (2022) Vol. 24, Iss. 2, pp. 211-211
Open Access | Times Cited: 44
Development of Wavelet Coherence EEG as a Biomarker for Diagnosis of Major Depressive Disorder
Danish M. Khan, Komal Masroor, Muhammad Fahim Mohd Jailani, et al.
IEEE Sensors Journal (2022) Vol. 22, Iss. 5, pp. 4315-4325
Closed Access | Times Cited: 39
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
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
DiffMDD: A Diffusion-Based Deep Learning Framework for MDD Diagnosis Using EEG
Yilin Wang, Sha Zhao, Haiteng Jiang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024) Vol. 32, pp. 728-738
Open Access | Times Cited: 10
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
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
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
Automated major depressive disorder detection using melamine pattern with EEG signals
Emrah Aydemir, Türker Tuncer, Şengül Doğan, et al.
Applied Intelligence (2021) Vol. 51, Iss. 9, pp. 6449-6466
Closed Access | Times Cited: 48
Exploring the Intrinsic Features of EEG Signals via Empirical Mode Decomposition for Depression Recognition
Jian Shen, Yanan Zhang, Huajian Liang, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022) Vol. 31, pp. 356-365
Open Access | Times Cited: 34
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
Mitigating the curse of dimensionality using feature projection techniques on electroencephalography datasets: an empirical review
Arti Anuragi, Dilip Singh Sisodia, Ram Bilas Pachori
Artificial Intelligence Review (2024) Vol. 57, Iss. 3
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
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
Improving EEG major depression disorder classification using FBSE coupled with domain adaptation method based machine learning algorithms
Hadeer Mohammed, Mohammed Diykh
Biomedical Signal Processing and Control (2023) Vol. 85, pp. 104923-104923
Open Access | Times Cited: 15
Application of Entropy for Automated Detection of Neurological Disorders With Electroencephalogram Signals: A Review of the Last Decade (2012–2022)
S. Janifer Jabin Jui, Ravinesh C. Deo, Prabal Datta Barua, et al.
IEEE Access (2023) Vol. 11, pp. 71905-71924
Open Access | Times Cited: 15
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