The application of artificial intelligence in improving colonoscopic adenoma detection rate: Where are we and where are we going

被引：5
作者：
Gan, Peiling [1 ]
Li, Peiling [1 ]
Xia, Huifang [1 ]
Zhou, Xian [1 ]
Tang, Xiaowei [1 ,2 ]
机构：
[1] Southwest Med Univ, Affiliated Hosp, Dept Gastroenterol, Luzhou, Peoples R China
[2] Chinese Peoples Liberat Army Gen Hosp, Med Ctr 1, Dept Gastroenterol, Beijing, Peoples R China
来源：
GASTROENTEROLOGIA Y HEPATOLOGIA | 2023年 / 46卷 / 03期
关键词：
Artificial intelligence; Adenoma detection rate; Convolutional neural networks; Computer-aided diagnosis; COMPUTER-AIDED DIAGNOSIS; COLORECTAL POLYP HISTOLOGY; LONGER WITHDRAWAL TIME; LEARNING ALGORITHM; MISS RATE; SYSTEM; CLASSIFICATION; LESIONS; ENDOCYTOSCOPY; ENDOSCOPY;
D O I：
10.1016/j.gastrohep.2022.03.009
中图分类号：
R57 [消化系及腹部疾病];
学科分类号：
摘要：
Colorectal cancer (CRC) is one of the common malignant tumors in the world. Colonoscopy is the crucial examination technique in CRC screening programs for the early detection of precursor lesions, and treatment of early colorectal cancer, which can reduce the morbidity and mortality of CRC significantly. However, pooled polyp miss rates during colonoscopic examination are as high as 22%. Artificial intelligence (AI) provides a promising way to improve the colonoscopic adenoma detection rate (ADR). It might assist endoscopists in avoiding missing polyps and offer an accurate optical diagnosis of suspected lesions. Herein, we described some of the milestone studies in using AI for colonoscopy, and the future application directions of AI in improving colonoscopic ADR. (c) 2022 Elsevier Espana, S.L.U. All rights reserved.
引用
收藏
页码：203 / 213
页数：11
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