Open Access Helper

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:

AMGCN-L: an adaptive multi-time-window graph convolutional network with long-short-term memory for depression detection
Han-Guang Wang, Qing‐Hao Meng, Li-Cheng Jin, et al.
Journal of Neural Engineering (2023) Vol. 20, Iss. 5, pp. 056038-056038
Closed Access | Times Cited: 9

Showing 9 citing articles:

MAST-GCN: Multi-Scale Adaptive Spatial-Temporal Graph Convolutional Network for EEG-Based Depression Recognition
Haifeng Lu, Zhiyang You, Yi Guo, et al.
IEEE Transactions on Affective Computing (2024) Vol. 15, Iss. 4, pp. 1985-1996
Closed Access | Times Cited: 5
A Review of Graph Theory-Based Diagnosis of Neurological Disorders Based on EEG and MRI
Ying Yan, Guanting Liu, Haoyang Cai, et al.
Neurocomputing (2024) Vol. 599, pp. 128098-128098
Closed Access | Times Cited: 5
Association of resting-state EEG with suicidality in depressed patients: a systematic review
Fatemeh Shamsi, Fatemeh Azadinia, Farzaneh Vafaee
BMC Psychiatry (2025) Vol. 25, Iss. 1
Open Access
Electrophysiological biomarkers based on CISANET characterize illness severity and suicidal ideation among patients with major depressive disorder
Yuchen Liang, Xuelin Gu, Yifan Shi, et al.
Medical & Biological Engineering & Computing (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
Early detection of depression through facial expression recognition and electroencephalogram-based artificial intelligence-assisted graphical user interface
Gajendra Kumar, Tanaya Das, Kuldeep Singh
Neural Computing and Applications (2024) Vol. 36, Iss. 12, pp. 6937-6954
Closed Access | Times Cited: 3
Spatio-temporal features based deep learning model for depression detection using two electrodes
Shubham Choudhary, Manish Kumar Bajpai, Kusum Kumari Bharti
Measurement Science and Technology (2024) Vol. 35, Iss. 8, pp. 086015-086015
Open Access | Times Cited: 2
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
Stacked ensemble machine learning approach for electroencephalography based major depressive disorder classification using temporal statistics
N. Ahmed, Tejas Kadengodlu Bhat, Omkar S Powar
Systems Science & Control Engineering (2024) Vol. 12, Iss. 1
Open Access
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