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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:

Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses
David Ahmedt‐Aristizabal, Tharindu Fernando, Simon Denman, et al.
IEEE Journal of Biomedical and Health Informatics (2020) Vol. 25, Iss. 1, pp. 69-76
Open Access | Times Cited: 84

Showing 1-25 of 84 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: 134
EEG-Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review
Ijaz Ahmad, Xin Wang, Mingxing Zhu, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-20
Open Access | Times Cited: 105
Application of data fusion for automated detection of children with developmental and mental disorders: A systematic review of the last decade
Smith K. Khare, Sonja March, Prabal Datta Barua, et al.
Information Fusion (2023) Vol. 99, pp. 101898-101898
Open Access | Times Cited: 78
Schizophrenia classification using machine learning on resting state EEG signal
Juan Ruiz de Miras, Antonio J. Ibáñez‐Molina, María Felipa Soriano, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104233-104233
Open Access | Times Cited: 76
Epilepsy detection in 121 patient populations using hypercube pattern from EEG signals
İrem Taşçı, Burak Taşçı, Prabal Datta Barua, et al.
Information Fusion (2023) Vol. 96, pp. 252-268
Closed Access | Times Cited: 57
Deep Learning Models for Diagnosis of Schizophrenia Using EEG Signals: Emerging Trends, Challenges, and Prospects
Rakesh Ranjan, Bikash Chandra Sahana, Ashish Kumar Bhandari
Archives of Computational Methods in Engineering (2024) Vol. 31, Iss. 4, pp. 2345-2384
Closed Access | Times Cited: 19
Electroencephalogram (EEG) Based Fuzzy Logic and Spiking Neural Networks (FLSNN) for Advanced Multiple Neurological Disorder Diagnosis
Shraddha Jain, Ruchi Srivastava
Brain Topography (2025) Vol. 38, Iss. 3
Closed Access | Times Cited: 2
Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls
Carla Barros, Carlos A. Silva, Ana P. Pinheiro
Artificial Intelligence in Medicine (2021) Vol. 114, pp. 102039-102039
Open Access | Times Cited: 80
Going deep into schizophrenia with artificial intelligence
Jose Cortes-Briones, Nicolas I. Tapia, Deepak Cyril D’Souza, et al.
Schizophrenia Research (2021) Vol. 245, pp. 122-140
Open Access | Times Cited: 70
EEG Signal Processing and Supervised Machine Learning to Early Diagnose Alzheimer’s Disease
Daniele Pirrone, Emanuel Weitschek, Primiano Di Paolo, et al.
Applied Sciences (2022) Vol. 12, Iss. 11, pp. 5413-5413
Open Access | Times Cited: 59
Multiview EEG signal analysis for diagnosis of schizophrenia: an optimized deep learning approach
Sweta Bhadra, Chandan Jyoti Kumar, Dhruba K. Bhattacharyya
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 14
Spectral features based convolutional neural network for accurate and prompt identification of schizophrenic patients
Kuldeep Singh, Sukhjeet Singh, Jyoteesh Malhotra
Proceedings of the Institution of Mechanical Engineers Part H Journal of Engineering in Medicine (2020) Vol. 235, Iss. 2, pp. 167-184
Closed Access | Times Cited: 70
Deep learning applied to electroencephalogram data in mental disorders: A systematic review
Mateo de Bardeci, Cheng-Teng Ip, Sebastian Olbrich
Biological Psychology (2021) Vol. 162, pp. 108117-108117
Open Access | Times Cited: 51
Automated accurate schizophrenia detection system using Collatz pattern technique with EEG signals
Mehmet Bayğın, Orhan Yaman, Türker Tuncer, et al.
Biomedical Signal Processing and Control (2021) Vol. 70, pp. 102936-102936
Closed Access | Times Cited: 51
A Survey on EEG Signal Processing Techniques and Machine Learning: Applications to the Neurofeedback of Autobiographical Memory Deficits in Schizophrenia
Miguel Á. Luján, María Verónica Jimeno Jiménez, Jorge Mateo, et al.
Electronics (2021) Vol. 10, Iss. 23, pp. 3037-3037
Open Access | Times Cited: 45
Automatic diagnosis of sleep apnea from biomedical signals using artificial intelligence techniques: Methods, challenges, and future works
Parisa Moridian, Afshin Shoeibi, Marjane Khodatars, et al.
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2022) Vol. 12, Iss. 6
Closed Access | Times Cited: 33
SCZ-SCAN: An automated Schizophrenia detection system from electroencephalogram signals
Geet Sahu, Mohan Karnati, Abhishek Gupta, et al.
Biomedical Signal Processing and Control (2023) Vol. 86, pp. 105206-105206
Closed Access | Times Cited: 21
Empowering precision medicine: AI-driven schizophrenia diagnosis via EEG signals: A comprehensive review from 2002–2023
Mahboobeh Jafari, Delaram Sadeghi, Afshin Shoeibi, et al.
Applied Intelligence (2023) Vol. 54, Iss. 1, pp. 35-79
Closed Access | Times Cited: 21
Hybrid Deep Learning Approach for Stress Detection Using Decomposed EEG Signals
Bishwajit Roy, Lokesh Malviya, Radhikesh Kumar, et al.
Diagnostics (2023) Vol. 13, Iss. 11, pp. 1936-1936
Open Access | Times Cited: 18
Automated detection of schizophrenia using deep learning: a review for the last decade
Manish Sharma, Ruchit Kumar Patel, Akshat Garg, et al.
Physiological Measurement (2023) Vol. 44, Iss. 3, pp. 03TR01-03TR01
Closed Access | Times Cited: 17
EEG-based classification of individuals with neuropsychiatric disorders using deep neural networks: A systematic review of current status and future directions
Mohsen Parsa, Habib Yousefi Rad, Hadi Vaezi, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 240, pp. 107683-107683
Closed Access | Times Cited: 17
Data leakage in deep learning studies of translational EEG
Geoffrey Brookshire, Jake Kasper, Nicholas M. Blauch, et al.
Frontiers in Neuroscience (2024) Vol. 18
Open Access | Times Cited: 7
From Sound Perception to Automatic Detection of Schizophrenia: An EEG-Based Deep Learning Approach
Carla Barros, Brian J. Roach, Judith M. Ford, et al.
Frontiers in Psychiatry (2022) Vol. 12
Open Access | Times Cited: 27
Automatic recognition of schizophrenia from brain-network features using graph convolutional neural network
Guimei Yin, Ying Chang, Yanli Zhao, et al.
Asian Journal of Psychiatry (2023) Vol. 87, pp. 103687-103687
Closed Access | Times Cited: 14
Exploring non-Euclidean relationships in EEG emotion recognition: A dynamic graph attention network
Rongrong Fu, Mengpu Cai, Shiwei Wang, et al.
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106276-106276
Closed Access | Times Cited: 5
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