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Articles Published Processes
6/30/2026 11:45:09 AM | Browse: 1 | Download: 11
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Received |
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2025-12-25 01:11 |
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Peer-Review Started |
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2025-12-25 01:11 |
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First Decision by Editorial Office Director |
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2026-01-22 07:20 |
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Return for Revision |
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2026-01-22 07:20 |
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Revised |
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2026-01-25 21:18 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-03-02 02:48 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-03-02 06:21 |
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Articles in Press |
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2026-03-02 06:21 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-06-15 00:17 |
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Publish the Manuscript Online |
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2026-06-30 11:45 |
| 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: https://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| 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 |
| Category |
Computer Science, Artificial Intelligence |
| Manuscript Type |
Review |
| Article Title |
Artificial intelligence for the diagnosis and treatment response prediction of obsessive-compulsive disorder: A narrative review
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Filiz Ozsoy, Gulay Tasci, Burak Tasci, Sengul Dogan and Turker Tuncer |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Burak Tasci, PhD, Vocational School of Technical Sciences, Firat University, Cahit Arf Street, Elazig 23119, Türkiye. btasci@firat.edu.tr |
| Key Words |
Obsessive-compulsive disorder; Artificial intelligence; Machine learning; Deep learning; Clinical decision support systems; Precision psychiatry; Neuroimaging; Treatment outcome; Explainable artificial intelligence |
| Core Tip |
This review highlights that artificial intelligence (AI) enables earlier and more accurate obsessive-compulsive disorder identification by integrating multimodal biomarkers (magnetic resonance imaging, electroencephalography, clinical scales, and digital phenotyping), surpassing unimodal models. Its key innovation is the joint clinical role of explainable AI for transparent neurobiological interpretation and large language models for personalized, scalable clinical decision support. Limited explainability, small samples, and weak external validation remain the main barriers to clinical translation. Future obsessive-compulsive disorder care requires multicenter, longitudinal, and clinician-aligned explainable AI systems to ensure ethical, regulatory, and trustworthy implementation. |
| Publish Date |
2026-06-30 11:45 |
| Citation |
Ozsoy F, Tasci G, Tasci B, Dogan S, Tuncer T. Artificial intelligence for the diagnosis and treatment response prediction of obsessive-compulsive disorder: A narrative review. World J Psychiatry 2026; 16(7): 118161
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| URL |
https://www.wjgnet.com/2220-3206/full/v16/i7/118161.htm |
| DOI |
https://doi.org/10.5498/wjp.118161 |
All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.
