Artificial intelligence applications in exposed endoscopic full-thickness resection vs thoracoscopic surgery for complex esophageal subepithelial lesions: Narrative review

doi:10.35712/aig.121906

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 7, Issue 2

This Article

(1)

(0)

(23)

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

Artificial Intelligence in Gastroenterology

ISSN

2644-3236

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Minireviews

Copyright: ©Author(s) 2026. 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.

Artif Intell Gastroenterol. Aug 8, 2026; 7(2): 121906
Published online Aug 8, 2026. doi: 10.35712/aig.121906

Table 1 Clinical outcomes: Exposed endoscopic full-thickness resection vs thoracoscopic surgery, n (%)/mean ± SD

Outcome	Exposed EFTR (n = 46)	TS (n = 46)	P value
Technical success	46 (100)	45 (97.8)	0.41
En bloc/R0 resection (%)	86.7	75.6	0.21
NG tube (days)	5.6 ± 2.1	10.7 ± 4.3	< 0.001
Hospital stay (days)	6.8 ± 1.9	12.3 ± 3.7	< 0.001
Recurrence (28 months) (%)	0	2.2	0.31

EFTR: Exposed endoscopic full-thickness resection; TS: Thoracoscopic surgery.

Full Size Table

Table 2 Published artificial intelligence performance metrics

Application	Study focus	Accuracy (%)	Latency
EUS lesion classification	Esophageal SELs	92
ESD phase recognition	Esophageal	92.1	30 milliseconds
ESD phase recognition	Esophageal	84.3	40 milliseconds
Robotic TS phase recognition	Thoracic surgery	82	50 milliseconds

Artificial intelligence performance metrics from multicenter validation studies. EUS: Endoscopic ultrasound; ESD: Endoscopic submucosal dissection; SEL: Subepithelial lesions; TS: Thoracoscopic surgery.

Full Size Table

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
URL: https://www.wjgnet.com/2644-3236/full/v7/i2/121906.htm
DOI: https://dx.doi.org/10.35712/aig.121906

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 [DOI: 10.35712/aig.121906]

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.