| ISSN |
1948-5190 (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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2023. 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 |
Meta-Analysis |
| Article Title |
Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Rômulo Sérgio Araújo Gomes, Guilherme Henrique Peixoto de Oliveira, Diogo Turiani Hourneaux de Moura, Ana Paula Samy Tanaka Kotinda, Carolina Ogawa Matsubayashi, Bruno Salomão Hirsch, Matheus de Oliveira Veras, João Guilherme Ribeiro Jordão Sasso, Roberto Paolo Trasolini, Wanderley Marques Bernardo and Eduardo Guimarães Hourneaux de Moura |
| Funding Agency and Grant Number |
|
| Corresponding Author |
Guilherme Henrique Peixoto de Oliveira, MD, Doctor, Doctor, Medical Assistant, Department of Gastroenterology, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, Dr Enéas de Carvalho Aguiar, 225, 6o Andar, Bloco 3, Cerqueira Cesar ZIP, São Paulo 05403-010, Brazil. dr.guilhermehpoliveira@gmail.com |
| Key Words |
Subepithelial lesions; Ultrasound endoscopy; Artificial intelligence |
| Core Tip |
Artificial intelligence (AI) has shown itself as a promising tool in diagnostic endoscopic ultrasound. This systematic review and meta-analysis analyze the diagnostic performance of endoscopy ultrasound with AI for subepithelial lesions and compare it with experienced endoscopists. Based on our meta-analysis, the endoscopy ultrasound assisted for AI has high diagnostic accuracy with superiority over experienced endoscopists. |
| Publish Date |
2023-08-10 08:07 |
| Citation |
Gomes RSA, de Oliveira GHP, de Moura DTH, Kotinda APST, Matsubayashi CO, Hirsch BS, Veras MO, Ribeiro Jordão Sasso JG, Trasolini RP, Bernardo WM, de Moura EGH. Endoscopic ultrasound artificial intelligence-assisted for prediction of gastrointestinal stromal tumors diagnosis: A systematic review and meta-analysis. World J Gastrointest Endosc 2023; 15(8): 528-539 |
| URL |
https://www.wjgnet.com/1948-5190/full/v15/i8/528.htm |
| DOI |
https://dx.doi.org/10.4253/wjge.v15.i8.528 |
