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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:

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: 33

Showing 1-25 of 33 citing articles:

Electroencephalography Signal Processing: A Comprehensive Review and Analysis of Methods and Techniques
Ahmad Chaddad, Yihang Wu, Reem Kateb, et al.
Sensors (2023) Vol. 23, Iss. 14, pp. 6434-6434
Open Access | Times Cited: 93
Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model
Umesh Kumar Lilhore, Surjeet Dalal, Neeraj Varshney, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 11
Ensemble graph neural network model for classification of major depressive disorder using whole-brain functional connectivity
V. Sujitha, Mikhail Votinov, Lisa Wagels, et al.
Frontiers in Psychiatry (2023) Vol. 14
Open Access | Times Cited: 14
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
Enhancing Depression Detection Using EEG Signals Through Adaptive Feature Weighting in Extra Trees Classifier
Challa Madhavi Latha, M. Kezia Joseph
Smart innovation, systems and technologies (2025), pp. 583-592
Closed Access
Automated Detection of Neurological and Mental Health Disorders Using EEG Signals and Artificial Intelligence: A Systematic Review
Hakan Uyanık, Abdulkadir Sengur, Massimo Salvi, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2025) Vol. 15, Iss. 1
Open Access
A Multiview Sparse Dynamic Graph Convolution-Based Region-Attention Feature Fusion Network for Major Depressive Disorder Detection
Weigang Cui, Mingyi Sun, Qunxi Dong, et al.
IEEE Transactions on Computational Social Systems (2023) Vol. 11, Iss. 2, pp. 2691-2702
Closed Access | Times Cited: 10
Depression assessment using integrated multi-featured EEG bands deep neural network models: Leveraging ensemble learning techniques
Kuo‐Hsuan Chung, Yue‐Shan Chang, Wei-Ting Yen, et al.
Computational and Structural Biotechnology Journal (2024) Vol. 23, pp. 1450-1468
Open Access | Times Cited: 3
EEGDepressionNet: A Novel Self Attention-Based Gated DenseNet With Hybrid Heuristic Adopted Mental Depression Detection Model Using EEG Signals
Mustufa Haider Abidi, Khaja Moiduddin, Rashid Ayub, et al.
IEEE Journal of Biomedical and Health Informatics (2024) Vol. 28, Iss. 9, pp. 5168-5179
Closed Access | Times Cited: 3
Meta-learning in Healthcare: A Survey
Alireza Rafiei, Ronald Moore, Sina Jahromi, et al.
SN Computer Science (2024) Vol. 5, Iss. 6
Closed Access | Times Cited: 3
A Multimodal Approach for Detection and Assessment of Depression Using Text, Audio and Video
Wei Zhang, Kaining Mao, Jie Chen
Phenomics (2024) Vol. 4, Iss. 3, pp. 234-249
Closed 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
A Robust Deep-Learning Model to Detect Major Depressive Disorder Utilising EEG Signals
Israq Ahmed Anik, A. H. M. Kamal, Muhammad Ashad Kabir, et al.
IEEE Transactions on Artificial Intelligence (2024) Vol. 5, Iss. 10, pp. 4938-4947
Closed Access | Times Cited: 1
Automated Major Depressive Disorder Classification using Deep Convolutional Neural Networks and Choquet Fuzzy Integral Fusion
Alireza Rafiei, Yu–Kai Wang
2021 IEEE Symposium Series on Computational Intelligence (SSCI) (2022)
Closed Access | Times Cited: 5
Non-Invasive Bio-Signal Data Classification Of Psychiatric Mood Disorders Using Modified CNN and VGG16
Berkan Ural
Uluslararası mühendislik araştırma ve geliştirme dergisi (2023) Vol. 15, Iss. 1, pp. 323-332
Open Access | Times Cited: 2
Clinical tools to detect Postpartum Depression based on Machine learning and EEG: A Review
Anagha Acharya, Ramya Ramesh, T.H. Hema A. Ayesha Fathima, et al.
(2023), pp. 1-8
Closed Access | Times Cited: 2
A novel time series classification for multivariate data using improved deep belief-recurrent neural network with optimal dynamic time warping
Bukya Mohan Babu, B. Sandhya
MATEC Web of Conferences (2024) Vol. 392, pp. 01161-01161
Open Access
The optimized Neural Networking scheme in Time Series Analysis for Detecting Depression
Megha Pandeya, Surjeet Yadav, R. Murugan
(2024), pp. 1-6
Closed Access
A Recurrence Plot-Based Graph Convolutional Network for Time Series Classification
Junghye Lee, Hyewon Kang, Taek-Ho Lee
(2024)
Closed Access
Electrode subset selection to lessen the complexity of brain activity measurement using EEG for depression detection
Shubham Choudhary, Manish Kumar Bajpai, Kusum Kumari Bharti
Transactions of the Institute of Measurement and Control (2024)
Closed Access
A Low-Complexity Combined Encoder-LSTM-Attention Networks for EEG-based Depression Detection
Noor Faris Ali, Nabil Albastaki, Abdelkader Nasreddine Belkacem, et al.
IEEE Access (2024) Vol. 12, pp. 129390-129403
Open Access
Major Depressive Disorder Detection Using Effective Connectivity of EEG Signals and Deep Learning Transformer Model
Nur Amira Ahmad Rezal, Norashikin Yahya, Farah Diana Azman, et al.
(2024), pp. 1-6
Closed Access
Multimodal Fusion of EEG and Audio Spectrogram for Major Depressive Disorder Recognition Using Modified DenseNet121
Musyyab Yousufi, Robertas Damaševičius, Rytis Maskeliūnas
Brain Sciences (2024) Vol. 14, Iss. 10, pp. 1018-1018
Open Access
An elevator door anomaly detection method based on improved deep multi-sphere support vector data description
Pengdong Xie, Linxuan Zhang, Minghong Li, et al.
Computers & Electrical Engineering (2024) Vol. 120, pp. 109660-109660
Closed Access
Perbandingan Metoda K-NN, Random Forest dan 1D CNN untuk Mengklasifikasi Data EEG Eye State
Muhammad Ibnu Choldun Rachmatullah, Aryaputra Wicaksono, Virdiandry Putratama
Journal of Information System Research (JOSH) (2023) Vol. 4, Iss. 2, pp. 669-675
Open Access | Times Cited: 1
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