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Articles Published Processes
7/10/2026 10:11:23 AM | Browse: 0 | Download: 0
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Received |
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2025-10-15 02:21 |
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Peer-Review Started |
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2025-10-15 02:21 |
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First Decision by Editorial Office Director |
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2025-11-10 07:11 |
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Return for Revision |
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2025-11-10 07:11 |
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Revised |
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2025-11-12 06:59 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-01-21 02:38 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-01-21 08:41 |
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Articles in Press |
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2026-01-21 08:41 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-03-29 03:06 |
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Publish the Manuscript Online |
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2026-07-10 10:11 |
| ISSN |
2222-0682 (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) 2026. Published by Baishideng Publishing Group Inc. All rights reserved. |
| 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 |
Ophthalmology |
| Manuscript Type |
Opinion Review |
| Article Title |
Artificial intelligence in ophthalmology: From diagnostic accuracy to clinical application
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Marco Zeppieri, Matteo Capobianco, Federico Visalli, Marieme Khouyyi, Mutali Musa, Alessandro Avitabile, Inferrera Leandro, Rosa Giglio, Daniele Tognetto, Caterina Gagliano, Fabiana D’Esposito and Francesco Cappellani |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Caterina Gagliano, MD, PhD, Department of Medicine and Surgery, Kore University of Enna, Viale delle Olimpiadi 1, Enna 94100, Italy. caterina.gagliano@unikore.it |
| Key Words |
Ophthalmology; Artificial intelligence; Image classification; Diagnostic precision; Clinical validation |
| Core Tip |
Artificial intelligence offers potential for enhancing ocular diagnoses; nevertheless, greater algorithmic accuracy at the image level rarely translates to improved patient outcomes. Obstacles, including data bias, domain shift, and label noise, coupled with a scarcity of prospective research and a lack of cost-effectiveness or equity evaluations, impede translation. Enhancing external validation, establishing predetermined thresholds, and incorporating human-factors engineering into healthcare workflows are imperative. Bridging this gap could convert algorithmic accuracy into significant diagnostic precision for glaucoma, diabetic retinopathy, and macular conditions. |
| Publish Date |
2026-07-10 10:11 |
| Citation |
Zeppieri M, Capobianco M, Visalli F, Khouyyi M, Musa M, Avitabile A, Leandro I, Giglio R, Tognetto D, Gagliano C, D’Esposito F, Cappellani F. Artificial intelligence in ophthalmology: From diagnostic accuracy to clinical application. World J Methodol 2026; 16(3): 115265
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| URL |
https://www.wjgnet.com/2222-0682/full/v16/i3/115265.htm |
| DOI |
https://doi.org/10.5662/wjm.115265 |
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