Impact of a real-time automatic quality control system on colorectal polyp and adenoma detection: a prospective randomized controlled study (with videos)

• Published in: Gastrointestinal endoscopy Vol. 91; no. 2; pp. 415 - 424.e4
• Main Authors: Su, Jing-Ran, Li, Zhen, Shao, Xue-Jun, Ji, Chao-Ran, Ji, Rui, Zhou, Ru-Chen, Li, Guang-Chao, Liu, Guan-Qun, He, Yi-Shan, Zuo, Xiu-Li, Li, Yan-Qing
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.02.2020
• Subjects: Adenoma - diagnosis; Adenoma - pathology; Adenomatous Polyps - diagnosis; Adenomatous Polyps - pathology; Adult; Automation; Colonic Polyps - diagnosis; Colonic Polyps - pathology; Colonoscopy - methods; Colonoscopy - standards; Colorectal Neoplasms - diagnosis; Colorectal Neoplasms - pathology; Computer Systems; Deep Learning; Early Detection of Cancer; Female; Humans; Image Processing, Computer-Assisted - methods; Male; Middle Aged; Neural Networks, Computer; Quality Control; CADe; DCNN; OR; CRC; CI; ROC; AI; BBPS; AQCS; ADR; PDR

Quality control can decrease variations in the performance of colonoscopists and improve the effectiveness of colonoscopy to prevent colorectal cancers. Unfortunately, routine quality control is difficult to carry out because a practical method is lacking. The aim of this study was to develop an aut...