Current status and limitations of artificial intelligence in colonoscopy

被引：37

作者：

Hann, Alexander ^{[1
]}

Troya, Joel ^{[1
]}

Fitting, Daniel ^{[1
]}

机构：

[1] Univ Hosp Wuerzburg, Intervent & Expt Endoscopy InExEn, Dept Internal Med 2, Wurzburg, Germany

来源：

UNITED EUROPEAN GASTROENTEROLOGY JOURNAL | 2021年 / 9卷 / 05期

关键词：

colonic polyps; colonoscopy; colorectal neoplasms; computer-assisted; deep learning; diagnosis; endoscopy; gastrointestinal; COMPUTER-AIDED DETECTION; DETECTION-ASSISTED COLONOSCOPY; SMALL COLORECTAL POLYPS; ADENOMA DETECTION RATE; GASTROINTESTINAL ENDOSCOPY; EUROPEAN-SOCIETY; CLASSIFICATION; DIAGNOSIS; SYSTEM; QUALITY;

D O I：

10.1002/ueg2.12108

中图分类号：

R57 [消化系及腹部疾病];

学科分类号：

摘要：

Background Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further efforts are needed to take CADx to the next level of development. Aim This work aims to give an overview of the current status of AI in colonoscopy, without going into too much technical detail. Methods A literature search to identify important studies exploring the use of AI in colonoscopy was performed. Results This review focuses on AI performance in screening colonoscopy summarizing the first prospective trials for CADe, the state of research in CADx as well as current limitations of those systems and legal issues.

引用

页码：527 / 533

页数：7

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