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Articles Published Processes
5/15/2025 10:28:49 AM | Browse: 14 | Download: 47
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Received |
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2024-11-14 10:57 |
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Peer-Review Started |
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2024-11-14 10:57 |
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To Make the First Decision |
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Return for Revision |
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2025-01-10 09:36 |
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Revised |
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2025-01-14 22:04 |
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Second Decision |
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2025-02-07 02:36 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-02-07 04:47 |
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Articles in Press |
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2025-02-07 04:47 |
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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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2025-04-27 08:55 |
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Publish the Manuscript Online |
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2025-05-15 10:28 |
| ISSN |
1948-5204 (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 |
The Author(s) 2025. 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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Letter to the Editor |
| Article Title |
Artificial intelligence as a predictive tool for gastric cancer: Bridging innovation, clinical translation, and ethical considerations
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Carlos M Ardila, Daniel González-Arroyave and Jaime Ramírez-Arbelaez |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Carlos M Ardila, Associate Professor, PhD, Postdoctoral Fellow, Professor, Department of Basic Sciences, Biomedical Stomatology Research Group, Faculty of Dentistry, Universidad de Antioquia U de A, Universidad de Antioquia, Calle 70 No. 52-21, Medellín 0057, Select State, Colombia. martin.ardila@udea.edu.co |
| Key Words |
Gastric cancer; Artificial intelligence; Machine learning; Deep learning; Predictive models |
| Core Tip |
Artificial intelligence (AI) is transforming gastric cancer management by enhancing early detection and individualized treatment planning through advanced predictive models. This letter highlights recent innovations in AI, such as a computed tomography-based radiomic model that predicts responses to neoadjuvant immunochemotherapy in advanced gastric cancer patients. By integrating AI-driven analysis with clinical factors, these tools offer substantial predictive accuracy, promising improved patient outcomes. However, to fully realize AI’s potential, ongoing collaboration is essential to address ethical, technical, and validation challenges, ensuring AI’s responsible integration into clinical oncology for effective, transparent, and patient-centered care. |
| Publish Date |
2025-05-15 10:28 |
| Citation |
<p>Ardila CM, González-Arroyave D, Ramírez-Arbelaez J. Artificial intelligence as a predictive tool for gastric cancer: Bridging innovation, clinical translation, and ethical considerations. <i>World J Gastrointest Oncol</i> 2025; 17(5): 103275</p> |
| URL |
https://www.wjgnet.com/1948-5204/full/v17/i5/103275.htm |
| DOI |
https://dx.doi.org/10.4251/wjgo.v17.i5.103275 |
© 2004-2025 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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