Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 major depressive disorder diagnosis approach based on EEG signals using dictionary learning and functional connectivity features
Reza Akbari Movahed, Gila Pirzad Jahromi, Shima Shahyad, et al.
Physical and Engineering Sciences in Medicine (2022) Vol. 45, Iss. 3, pp. 705-719
Closed Access | Times Cited: 9

Showing 9 citing articles:

EEG-based functional connectivity analysis of brain abnormalities: A systematic review study
Nastaran Khaleghi, Shaghayegh Hashemi, Mohammad Peivandi, et al.
Informatics in Medicine Unlocked (2024) Vol. 47, pp. 101476-101476
Open Access | Times Cited: 7
Machine learning approaches for diagnosing depression using EEG: A review
Yuan Liu, Changqin Pu, Shan Xia, et al.
Translational Neuroscience (2022) Vol. 13, Iss. 1, pp. 224-235
Open Access | Times Cited: 24
Resting-State Electroencephalogram Depression Diagnosis Based on Traditional Machine Learning and Deep Learning: A Comparative Analysis
Haijun Lin, Jing Fang, Junpeng Zhang, et al.
Sensors (2024) Vol. 24, Iss. 21, pp. 6815-6815
Open Access | Times Cited: 2
Breakdown of long-range spatial correlations of infraslow amplitude fluctuations of EEG oscillations in patients with current and past major depressive disorder
Duho Sihn, Ji Sun Kim, Oh‐Sang Kwon, et al.
Frontiers in Psychiatry (2023) Vol. 14
Open Access | Times Cited: 5
Machine Learning Model for Computer‐Aided Depression Screening among Young Adults Using Wireless EEG Headset
Nazmus Sakib, Md. Kafiul Islam, Tasnuva Faruk
Computational Intelligence and Neuroscience (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 5
A Multi-stream Deep Learning Model for EEG-based Depression Identification
Hao Wu, Jiyao Liu
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2022), pp. 2029-2034
Closed Access | Times Cited: 6
A Functional Connectivity-Based Model with a Lightweight Attention Mechanism for Depression Recognition Using EEG signals
Ming Ying, Jing Zhu, Xiaowei Li, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024) Vol. 32, pp. 4240-4248
Open Access
Cross-domain transferable discriminant dictionary based sparse representation approach for EEG emotion-level recognition
Tongguang Ni, Chengbing He, Yizhang Jiang, et al.
International Journal of Machine Learning and Cybernetics (2023) Vol. 15, Iss. 3, pp. 1087-1099
Closed Access | Times Cited: 1
Effect of Artifact Removal in Machine Learning Based Depression Screening using EEG
Nazmus Sakib, Md. Kafiul Islam, Tasnuva Faruk
(2023) Vol. 24, pp. 115-120
Closed Access
Page 1

Scroll to top