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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:

Classification Methods Based on Complexity and Synchronization of Electroencephalography Signals in Alzheimer’s Disease
Sou Nobukawa, Teruya Yamanishi, Shinya Kasakawa, et al.
Frontiers in Psychiatry (2020) Vol. 11
Open Access | Times Cited: 72

Showing 1-25 of 72 citing articles:

Graph Neural Network-Based EEG Classification: A Survey
Dominik Klepl, Min Wu, Fei He
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024) Vol. 32, pp. 493-503
Open Access | Times Cited: 18
EEG-Based Graph Neural Network Classification of Alzheimer’s Disease: An Empirical Evaluation of Functional Connectivity Methods
Dominik Klepl, Fei He, Min Wu, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2022) Vol. 30, pp. 2651-2660
Open Access | Times Cited: 40
IoT-driven augmented reality and virtual reality systems in neurological sciences
Mehar Sahu, Rohan Gupta, Rashmi K. Ambasta, et al.
Internet of Things (2024) Vol. 25, pp. 101098-101098
Closed Access | Times Cited: 11
Exploring Rhythms and Channels-Based EEG Biomarkers for Early Detection of Alzheimer's Disease
Siuly Siuly, Ömer Faruk Alçin, Hua Wang, et al.
IEEE Transactions on Emerging Topics in Computational Intelligence (2024) Vol. 8, Iss. 2, pp. 1609-1623
Closed Access | Times Cited: 9
Spatial–temporal graph convolutional network for Alzheimer classification based on brain functional connectivity imaging of electroencephalogram
Xiaocai Shan, Jun Cao, Shoudong Huo, et al.
Human Brain Mapping (2022) Vol. 43, Iss. 17, pp. 5194-5209
Open Access | Times Cited: 32
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
EEG-Based Brain Functional Network Analysis for Differential Identification of Dementia-Related Disorders and Their Onset
Abdulyekeen T. Adebisi, Ho‐Won Lee, Kalyana C. Veluvolu
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2024) Vol. 32, pp. 1198-1209
Open Access | Times Cited: 7
EEG entropy insights in the context of physiological aging and Alzheimer’s and Parkinson’s diseases: a comprehensive review
Alessia Cacciotti, Chiara Pappalettera, Francesca Miraglia, et al.
GeroScience (2024) Vol. 46, Iss. 6, pp. 5537-5557
Open Access | Times Cited: 7
Diagnosis of Alzheimer’s Disease by Time-Dependent Power Spectrum Descriptors and Convolutional Neural Network Using EEG Signal
Morteza Amini, Mir Mohsen Pedram, Alireza Moradi, et al.
Computational and Mathematical Methods in Medicine (2021) Vol. 2021, pp. 1-17
Open Access | Times Cited: 38
Identification of Electroencephalogram Signals in Alzheimer's Disease by Multifractal and Multiscale Entropy Analysis
Momo Ando, Sou Nobukawa, Mitsuru Kikuchi, et al.
Frontiers in Neuroscience (2021) Vol. 15
Open Access | Times Cited: 34
Application of Entropy for Automated Detection of Neurological Disorders With Electroencephalogram Signals: A Review of the Last Decade (2012–2022)
S. Janifer Jabin Jui, Ravinesh C. Deo, Prabal Datta Barua, et al.
IEEE Access (2023) Vol. 11, pp. 71905-71924
Open Access | Times Cited: 15
A review of Graph Neural Networks for Electroencephalography data analysis
Manuel Graña, Igone Morais-Quilez
Neurocomputing (2023) Vol. 562, pp. 126901-126901
Open Access | Times Cited: 15
Diagnose Alzheimer’s disease and mild cognitive impairment using deep CascadeNet and handcrafted features from EEG signals
Khosro Rezaee, Min Zhu
Biomedical Signal Processing and Control (2024) Vol. 99, pp. 106895-106895
Closed Access | Times Cited: 5
An EEG-based framework for automated discrimination of conversion to Alzheimer’s disease in patients with amnestic mild cognitive impairment: an 18-month longitudinal study
Yingfeng Ge, Jianan Yin, Caie Chen, et al.
Frontiers in Aging Neuroscience (2025) Vol. 16
Open Access
Detection of neonatal asphyxia by analyzing the complexity of electroencephalography data
Sou Nobukawa, Kurnianingsih, Isshu Wakita, et al.
Frontiers in Applied Mathematics and Statistics (2025) Vol. 11
Open Access
A Review of Methods of Diagnosis and Complexity Analysis of Alzheimer’s Disease Using EEG Signals
Mahshad Ouchani, Shahriar Gharibzadeh, Mahdieh Jamshidi, et al.
BioMed Research International (2021) Vol. 2021, pp. 1-15
Open Access | Times Cited: 31
Identification of attention-deficit hyperactivity disorder based on the complexity and symmetricity of pupil diameter
Sou Nobukawa, Aya Shirama, Tetsuya Takahashi, et al.
Scientific Reports (2021) Vol. 11, Iss. 1
Open Access | Times Cited: 29
Adaptive Gated Graph Convolutional Network for Explainable Diagnosis of Alzheimer’s Disease Using EEG Data
Dominik Klepl, Fei He, Min Wu, et al.
IEEE Transactions on Neural Systems and Rehabilitation Engineering (2023) Vol. 31, pp. 3978-3987
Open Access | Times Cited: 11
A deep learning framework for identifying Alzheimer's disease using fMRI-based brain network
Ruofan Wang, Qiguang He, Chunxiao Han, et al.
Frontiers in Neuroscience (2023) Vol. 17
Open Access | Times Cited: 10
Synchronization of Chaos in Neural Systems
Sou Nobukawa, H. Nishimura
Frontiers in Applied Mathematics and Statistics (2020) Vol. 6
Open Access | Times Cited: 22
Machine and Deep Learning Trends in EEG-Based Detection and Diagnosis of Alzheimer’s Disease: A Systematic Review
Marcos Avilés, Luz-María Sánchez, José M. Álvarez-Alvarado, et al.
Eng—Advances in Engineering (2024) Vol. 5, Iss. 3, pp. 1464-1484
Open Access | Times Cited: 2
High Phase Synchronization in Alpha Band Activity in Older Subjects With High Creativity
Sou Nobukawa, Teruya Yamanishi, Kanji Ueno, et al.
Frontiers in Human Neuroscience (2020) Vol. 14
Open Access | Times Cited: 20
A Pilot Study on Visually Stimulated Cognitive Tasks for EEG-Based Dementia Recognition
Supavit Kongwudhikunakorn, Suktipol Kiatthaveephong, Kamonwan Thanontip, et al.
IEEE Transactions on Instrumentation and Measurement (2021) Vol. 70, pp. 1-10
Open Access | Times Cited: 17
ANALYSIS OF THE CORRELATION BETWEEN EYES AND BRAIN ACTIVITIES IN RESPONSE TO MOVING VISUAL STIMULI
Ramesh Ramamoorthy, Avinash Menon, Karthikeyan Rajagopal, et al.
Fractals (2021) Vol. 29, Iss. 08
Open Access | Times Cited: 17
Evaluation of the coupling among visual stimuli, eye fluctuations, and brain signals
Avinash Menon, Ondřej Krejcar, Hamidreza Namazi
Chaos Solitons & Fractals (2021) Vol. 153, pp. 111492-111492
Open Access | Times Cited: 16
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