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Articles Published Processes
3/19/2026 7:07:29 AM | Browse: 0 | Download: 0
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Received |
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2025-10-31 05:40 |
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Peer-Review Started |
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2025-10-31 05:40 |
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First Decision by Editorial Office Director |
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2025-11-18 11:11 |
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Return for Revision |
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2025-11-18 11:11 |
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Revised |
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2025-11-29 05:04 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-01-22 02:37 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-01-22 10:49 |
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Articles in Press |
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2026-01-22 10:49 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-02-28 08:00 |
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Publish the Manuscript Online |
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2026-03-19 07:07 |
| ISSN |
1007-9327 (print) and 2219-2840 (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) 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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Minireviews |
| Article Title |
Artificial intelligence-assisted endoscopy in the detection of early gastrointestinal cancer: Progress, challenges, and future directions
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Zhong-Xing Ning, Jia-Jia Xiao and Zi-Xiong Zhou |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| School level project of Guangxi Vocational and Technical College |
No. 231208 |
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| Corresponding Author |
Zi-Xiong Zhou, School of Economics and Management, Shanghai Institute of Technology, No. 120 Caobao Road, Xuhui District, Shanghai 200235, China. zozixoo@163.com |
| Key Words |
Artificial intelligence; Gastrointestinal endoscopy; Early cancer detection; Deep learning; Computer-aided diagnosis |
| Core Tip |
Artificial intelligence (AI)-assisted endoscopy technologies have significantly advanced early detection and diagnosis of gastrointestinal cancers, enhancing adenoma detection rates and improving clinical outcomes. Recent studies demonstrate that AI, through deep learning models, can effectively identify small lesions, reduce missed diagnoses, and assist in clinical decision-making across various gastrointestinal regions, including the esophagus, stomach, and colon. However, challenges such as data quality, model generalization, and physician-AI collaboration remain. Overcoming these issues will ensure AI’s broader clinical integration, making it a vital tool in precision medicine and early cancer screening. |
| Publish Date |
2026-03-19 07:07 |
| Citation |
Ning ZX, Xiao JJ, Zhou ZX. Artificial intelligence-assisted endoscopy in the detection of early gastrointestinal cancer: Progress, challenges, and future directions. World J Gastroenterol 2026; 32(12): 115990 |
| URL |
https://www.wjgnet.com/1007-9327/full/v32/i12/115990.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v32.i12.115990 |
© 1993-2026 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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