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8/6/2026 7:34:30 AM | Browse: 0 | Download: 0
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Received |
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2026-04-07 07:33 |
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Peer-Review Started |
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2026-04-07 07:36 |
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First Decision by Editorial Office Director |
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2026-04-30 00:29 |
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Return for Revision |
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2026-04-30 00:29 |
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Revised |
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2026-05-14 00:42 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-06-11 02:39 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-06-11 07:29 |
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Articles in Press |
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2026-06-11 07:29 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-07-06 02:33 |
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Publish the Manuscript Online |
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2026-08-06 07:34 |
| ISSN |
2644-3236 (online) |
| Open Access |
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Minireviews |
| Article Title |
Artificial intelligence applications in exposed endoscopic full-thickness resection vs thoracoscopic surgery for complex esophageal subepithelial lesions: Narrative review
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Gemechu Dereje Feyissa |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Gemechu Dereje Feyissa, Assistant Professor, Department of Public Health, Faculty of Health Sciences, Rift Valley University, Hangatu District, Dabe Sub-City, Adama 1715, Oromīa, Ethiopia. gemechudereje80@gmail.com |
| Key Words |
Artificial intelligence; Endoscopic full-thickness resection; Thoracoscopic surgery; Subepithelial lesions; Esophageal tumors; Machine learning; Endoscopic ultrasound; Computer-aided detection |
| Core Tip |
Artificial intelligence holds promise for esophageal subepithelial lesion management through endoscopic ultrasound characterization, exposed endoscopic full-thickness resection workflow support, and thoracoscopic surgery navigation; evidence is primarily adjacent/transferable, warranting procedure-specific validation. |
| Publish Date |
2026-08-06 07:34 |
| Citation |
Feyissa GD. Artificial intelligence applications in exposed endoscopic full-thickness resection vs thoracoscopic surgery for complex esophageal subepithelial lesions: Narrative review. Artif Intell Gastroenterol 2026; 7(2): 121906
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| URL |
https://www.wjgnet.com/2644-3236/full/v7/i2/121906.htm |
| DOI |
https://doi.org/10.35712/aig.121906 |
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