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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:

Brain functional connectivity patterns for emotional state classification in Parkinson’s disease patients without dementia
Rajamanickam Yuvaraj, M. Murugappan, U. Rajendra Acharya, et al.
Behavioural Brain Research (2015) Vol. 298, pp. 248-260
Closed Access | Times Cited: 149

Showing 1-25 of 149 citing articles:

Automated EEG-based screening of depression using deep convolutional neural network
U. Rajendra Acharya, Shu Lih Oh, Yuki Hagiwara, et al.
Computer Methods and Programs in Biomedicine (2018) Vol. 161, pp. 103-113
Closed Access | Times Cited: 536
Review and Classification of Emotion Recognition Based on EEG Brain-Computer Interface System Research: A Systematic Review
Abeer Al-Nafjan, Manar Hosny, Yousef Al-Ohali, et al.
Applied Sciences (2017) Vol. 7, Iss. 12, pp. 1239-1239
Open Access | Times Cited: 249
Parkinson's disease: Cause factors, measurable indicators, and early diagnosis
Shreya Bhat, U. Rajendra Acharya, Yuki Hagiwara, et al.
Computers in Biology and Medicine (2018) Vol. 102, pp. 234-241
Closed Access | Times Cited: 170
Self-Supervised Learning for Electroencephalography
Mohammad Hossein Rafiei, Lynne V. Gauthier, Hojjat Adeli, et al.
IEEE Transactions on Neural Networks and Learning Systems (2022) Vol. 35, Iss. 2, pp. 1457-1471
Closed Access | Times Cited: 161
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
Brain functional and effective connectivity based on electroencephalography recordings: A review
Jun Cao, Yifan Zhao, Xiaocai Shan, et al.
Human Brain Mapping (2021) Vol. 43, Iss. 2, pp. 860-879
Open Access | Times Cited: 139
Anaphylaxis: A 2023 practice parameter update
David B.K. Golden, Julie Wang, Susan Waserman, et al.
Annals of Allergy Asthma & Immunology (2023) Vol. 132, Iss. 2, pp. 124-176
Open Access | Times Cited: 87
Developing an EEG-Based Emotion Recognition Using Ensemble Deep Learning Methods and Fusion of Brain Effective Connectivity Maps
Sara Bagherzadeh, Ahmad Shalbaf, Afshin Shoeibi, et al.
IEEE Access (2024) Vol. 12, pp. 50949-50965
Open Access | Times Cited: 15
Graph Theory and Brain Connectivity in Alzheimer’s Disease
Jon delEtoile, Hojjat Adeli
The Neuroscientist (2017) Vol. 23, Iss. 6, pp. 616-626
Closed Access | Times Cited: 165
Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders
U. Raghavendra, U. Rajendra Acharya, Hojjat Adeli
European Neurology (2019) Vol. 82, Iss. 1-3, pp. 41-64
Open Access | Times Cited: 131
Impact of the reference choice on scalp EEG connectivity estimation
Federico Chella, Vittorio Pizzella, Filippo Zappasodi, et al.
Journal of Neural Engineering (2016) Vol. 13, Iss. 3, pp. 036016-036016
Open Access | Times Cited: 116
Automated detection of Parkinson's disease using minimum average maximum tree and singular value decomposition method with vowels
Türker Tuncer, Şengül Doğan, U. Rajendra Acharya
Journal of Applied Biomedicine (2019) Vol. 40, Iss. 1, pp. 211-220
Closed Access | Times Cited: 104
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: 99
Convolutional Neural Networks for Neuroimaging in Parkinson’s Disease: Is Preprocessing Needed?
Francisco J. Martínez-Murcia, J. M. Górriz, Javier Ramı́rez, et al.
International Journal of Neural Systems (2018) Vol. 28, Iss. 10, pp. 1850035-1850035
Open Access | Times Cited: 96
Ten challenges for EEG-based affective computing
Xin Hu, Jingjing Chen, Fei Wang, et al.
Brain Science Advances (2019) Vol. 5, Iss. 1, pp. 1-20
Open Access | Times Cited: 88
GaborPDNet: Gabor Transformation and Deep Neural Network for Parkinson’s Disease Detection Using EEG Signals
Hui Wen Loh, Chui Ping Ooi, Elizabeth E. Palmer, et al.
Electronics (2021) Vol. 10, Iss. 14, pp. 1740-1740
Open Access | Times Cited: 87
Application of Deep Learning Models for Automated Identification of Parkinson’s Disease: A Review (2011–2021)
Hui Wen Loh, Wanrong Hong, Chui Ping Ooi, et al.
Sensors (2021) Vol. 21, Iss. 21, pp. 7034-7034
Open Access | Times Cited: 80
Deep Learning Classification of Neuro-Emotional Phase Domain Complexity Levels Induced by Affective Video Film Clips
Serap Aydın
IEEE Journal of Biomedical and Health Informatics (2019) Vol. 24, Iss. 6, pp. 1695-1702
Closed Access | Times Cited: 78
Detection of Parkinson’s disease using automated tunable Q wavelet transform technique with EEG signals
Smith K. Khare, Varun Bajaj, U. Rajendra Acharya
Journal of Applied Biomedicine (2021) Vol. 41, Iss. 2, pp. 679-689
Closed Access | Times Cited: 71
EEG-based emotion charting for Parkinson's disease patients using Convolutional Recurrent Neural Networks and cross dataset learning
Muhammad Najam Dar, Muhammad Usman Akram, Rajamanickam Yuvaraj, et al.
Computers in Biology and Medicine (2022) Vol. 144, pp. 105327-105327
Closed Access | Times Cited: 42
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: 8
A pathological brain detection system based on kernel based ELM
Siyuan Lu, Zhihai Lu, Jianfei Yang, et al.
Multimedia Tools and Applications (2016) Vol. 77, Iss. 3, pp. 3715-3728
Closed Access | Times Cited: 65
Emotion Recognition and Dynamic Functional Connectivity Analysis Based on EEG
Xucheng Liu, Ting Li, Cong Tang, et al.
IEEE Access (2019) Vol. 7, pp. 143293-143302
Open Access | Times Cited: 59
Early diagnosis of Parkinson’s disease using EEG, machine learning and partial directed coherence
Ana Paula S. Oliveira, Maí­ra Araújo de Santana, Maria Karoline S. Andrade, et al.
Research on Biomedical Engineering (2020) Vol. 36, Iss. 3, pp. 311-331
Closed Access | Times Cited: 51
Machine Learning Methods with Decision Forests for Parkinson’s Detection
Moumita Pramanik, Ratika Pradhan, Parvati Nandy, et al.
Applied Sciences (2021) Vol. 11, Iss. 2, pp. 581-581
Open Access | Times Cited: 44
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