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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:

Examining Effects of Schizophrenia on EEG with Explainable Deep Learning Models
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, et al.
(2022)
Open Access | Times Cited: 29

Showing 1-25 of 29 citing articles:

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: 16
Responsible Artificial Intelligence for Mental Health Disorders: Current Applications and Future Challenges
Shaker El–Sappagh, Waleed Nazih, Meshal Alharbi, et al.
Deleted Journal (2025) Vol. 4, Iss. 1
Closed Access | Times Cited: 1
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: 17
A Framework for Systematically Evaluating the Representations Learned by A Deep Learning Classifier from Raw Multi-Channel Electroencephalogram Data
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 13
Towards greater neuroimaging classification transparency via the integration of explainability methods and confidence estimation approaches
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
Informatics in Medicine Unlocked (2023) Vol. 37, pp. 101176-101176
Open Access | Times Cited: 12
Examining Reproducibility of EEG Schizophrenia Biomarkers Across Explainable Machine Learning Models
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, et al.
(2022)
Open Access | Times Cited: 19
Explainable fuzzy clustering framework reveals divergent default mode network connectivity dynamics in schizophrenia
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
Frontiers in Psychiatry (2024) Vol. 15
Open Access | Times Cited: 2
Transfer Learning for the Identification of Paediatric EEGs With Interictal Epileptiform Abnormalities
Lan Wei, John C. McHugh, Catherine Mooney
IEEE Access (2024) Vol. 12, pp. 86073-86082
Open Access | Times Cited: 2
Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures
Charles A. Ellis, Martina Lapera Sancho, Robyn L. Miller, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
Novel Approach Explains Spatio-Spectral Interactions In Raw Electroencephalogram Deep Learning Classifiers
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, et al.
(2023), pp. 1-5
Open Access | Times Cited: 5
A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis*
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2023)
Closed Access | Times Cited: 5
Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data*
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, et al.
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023)
Closed Access | Times Cited: 5
Improving Multichannel Raw Electroencephalography-based Diagnosis of Major Depressive Disorder via Transfer Learning with Single Channel Sleep Stage Data*
Charles A. Ellis, Abhinav Sattiraju, Robyn L. Miller, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 4
Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
(2024), pp. 1-5
Open Access | Times Cited: 1
Cross-Sampling Rate Transfer Learning for Enhanced Raw EEG Deep Learning Classifier Performance in Major Depressive Disorder Diagnosis
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 3
Improving Explainability for Single-Channel EEG Deep Learning Classifiers via Interpretable Filters and Activation Analysis*
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (2023)
Open Access | Times Cited: 3
A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations *
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (2023), pp. 1-4
Closed Access | Times Cited: 2
Evaluating Augmentation Approaches for Deep Learning-based Major Depressive Disorder Diagnosis with Raw Electroencephalogram Data*
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 2
An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis
Abhinav Sattiraju, Charles A. Ellis, Robyn L. Miller, et al.
(2023)
Open Access | Times Cited: 2
From Brain Waves to Diagnoses: AI's Role in Schizophrenia Detection
N Shan, V. Amsaveni
(2024), pp. 1-5
Closed Access
Identifying EEG Biomarkers of Depression with Novel Explainable Deep Learning Architectures
Charles A. Ellis, Martina Lapera Sancho, Robyn L. Miller, et al.
Communications in computer and information science (2024), pp. 102-124
Closed Access
Efficient Schizophrenia Detection Through Transfer Learning for Robust Diagnostics
Gnaneswari Kancherla, Srinivasa Panchavedi Gopamsana, Bhaskar Reddy Yadamakanti, et al.
(2024), pp. 318-327
Closed Access
Schizophrenia Detection Using EEG: A Study on Frequency Relevance
Luı́s A. Alexandre, Włodzisław Duch
2022 IEEE Congress on Evolutionary Computation (CEC) (2024), pp. 01-08
Closed Access
Exploration of an intrinsically explainable self-attention based model for prototype generation on single-channel EEG sleep stage classification
Brenton Adey, Ahsan Habib, Chandan Karmakar
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
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