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Articles in Press
6/30/2025 9:44:57 AM | Browse: 6 | Download: 0
Category |
Computer Science, Artificial Intelligence |
Manuscript Type |
Observational Study |
Article Title |
Self-AttentionNeXt: Exploring schizophrenic optical coherence tomography image detection investigations
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Manuscript Source |
Invited Manuscript |
All Author List |
Mehmet Kaan Kaya, Sermal Arslan, Suheda Kaya, Gulay Tasci, Burak Tasci, Filiz Ozsoy, Sengul Dogan and Turker Tuncer |
Funding Agency and Grant Number |
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Corresponding Author |
Sengul Dogan, Professor, Department of Digital Forensics Engineering, College of Technology, Firat University, University district, Elazig 23119, Türkiye. sdogan@firat.edu.tr |
Key Words |
Self-AttentionNeXt; Optical coherence tomography image classification; Schizophrenia detection; Biomedical image classification; Deep learning in ophthalmology; Retinal imaging biomarkers |
Core Tip |
This study presents Self-AttentionNeXt, a novel deep learning architecture that integrates self-attention mechanisms from transformer models with convolutional neural networks for the classification of optical coherence tomography images. By focusing on retinal image regions most relevant to schizophrenia, the model achieves high diagnostic accuracy. The integration of inverted bottleneck attention blocks and residual connections enhances both feature representation and training stability. Self-AttentionNeXt demonstrates that combining attention mechanisms with convolutional neural networks can offer a powerful tool for supporting ophthalmic evaluation in patients with schizophrenia. |
Citation |
Kaya MK, Arslan S, Kaya S, Tasci G, Tasci B, Ozsoy F, Dogan S, Tuncer T. Self-AttentionNeXt: Exploring schizophrenic optical coherence tomography image detection investigations. World J Psychiatry 2025; In press |
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Received |
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2025-04-13 11:50 |
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Peer-Review Started |
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2025-04-21 00:19 |
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To Make the First Decision |
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Return for Revision |
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2025-05-12 02:25 |
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Revised |
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2025-05-16 08:36 |
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Second Decision |
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2025-06-23 11:35 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-06-30 09:44 |
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Articles in Press |
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2025-06-30 09:44 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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ISSN |
2220-3206 (online) |
Open Access |
This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/ |
Copyright |
© The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
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