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

doi:10.35712/aig.121906

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Artificial Intelligence in Gastroenterology

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2644-3236

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

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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 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.

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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]

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