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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:

DepHNN: A novel hybrid neural network for electroencephalogram (EEG)-based screening of depression
Geetanjali Sharma, Abhishek Parashar, Amit M. Joshi
Biomedical Signal Processing and Control (2021) Vol. 66, pp. 102393-102393
Closed Access | Times Cited: 141

Showing 1-25 of 141 citing articles:

Automatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models
Afshin Shoeibi, Delaram Sadeghi, Parisa Moridian, et al.
Frontiers in Neuroinformatics (2021) Vol. 15
Open Access | Times Cited: 128
Electroencephalography-based motor imagery classification using temporal convolutional network fusion
Yazeed K. Musallam, Nasser I. AlFassam, Ghulam Muhammad, et al.
Biomedical Signal Processing and Control (2021) Vol. 69, pp. 102826-102826
Closed Access | Times Cited: 126
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
Emerging Trends in EEG Signal Processing: A Systematic Review
Ramnivas Sharma, Hemant Kumar Meena
SN Computer Science (2024) Vol. 5, Iss. 4
Closed Access | Times Cited: 23
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
Exploration of EEG-Based Depression Biomarkers Identification Techniques and Their Applications: A Systematic Review
Antora Dev, N. Roy, Md. Kafiul Islam, et al.
IEEE Access (2022) Vol. 10, pp. 16756-16781
Open Access | Times Cited: 56
Depression diagnosis by deep learning using EEG signals: A systematic review
Atefeh Safayari, Hamidreza Bolhasani
Medicine in Novel Technology and Devices (2021) Vol. 12, pp. 100102-100102
Open Access | Times Cited: 56
Parkinson’s disease diagnosis and stage prediction based on gait signal analysis using EMD and CNN–LSTM network
B. Vidya, P. Sasikumar
Engineering Applications of Artificial Intelligence (2022) Vol. 114, pp. 105099-105099
Closed Access | Times Cited: 41
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
Electroencephalography-Based Depression Detection Using Multiple Machine Learning Techniques
Amel Ksibi, Mohammed Zakariah, Leila Jamel, et al.
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1779-1779
Open Access | Times Cited: 33
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
Convolutional Neural Network-Based EEG Signal Analysis: A Systematic Review
Swati Rajwal, Swati Aggarwal
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 6, pp. 3585-3615
Closed Access | Times Cited: 23
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: 11
A comprehensive review of predictive analytics models for mental illness using machine learning algorithms
Md. Monirul Islam, Shahriar Hassan, Sharmin Akter, et al.
Healthcare Analytics (2024) Vol. 6, pp. 100350-100350
Open Access | Times Cited: 8
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
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: 52
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: 49
A Depression Prediction Algorithm Based on Spatiotemporal Feature of EEG Signal
Wei Liu, Kebin Jia, Zhuozheng Wang, et al.
Brain Sciences (2022) Vol. 12, Iss. 5, pp. 630-630
Open Access | Times Cited: 35
Benchmarks for machine learning in depression discrimination using electroencephalography signals
Ayan Seal, Rishabh Bajpai, Mohan Karnati, et al.
Applied Intelligence (2022) Vol. 53, Iss. 10, pp. 12666-12683
Closed Access | Times Cited: 28
A novel hybrid model in the diagnosis and classification of Alzheimer's disease using EEG signals: Deep ensemble learning (DEL) approach
Majid Nour, Ümit Şentürk, Kemal Polat
Biomedical Signal Processing and Control (2023) Vol. 89, pp. 105751-105751
Closed Access | Times Cited: 20
GDilatedDTA: Graph dilation convolution strategy for drug target binding affinity prediction
Longxin Zhang, Wenliang Zeng, Jingsheng Chen, et al.
Biomedical Signal Processing and Control (2024) Vol. 92, pp. 106110-106110
Closed Access | Times Cited: 7
EDT: An EEG-based attention model for feature learning and depression recognition
Ming Ying, Xuexiao Shao, Jing Zhu, et al.
Biomedical Signal Processing and Control (2024) Vol. 93, pp. 106182-106182
Closed Access | Times Cited: 6
Depression signal correlation identification from different EEG channels based on CNN feature extraction
Baiyang Wang, Yuyun Kang, Dongyue Huo, et al.
Psychiatry Research Neuroimaging (2022) Vol. 328, pp. 111582-111582
Closed Access | Times Cited: 24
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
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