Globally, colorectal cancer is the third most diagnosed malignancy. It causes significant
mortality and morbidity, which can be reduced by early diagnosis with an effective screening …

Background Recent prospective randomized controlled trials have evaluated deep
convolutional neural network (CNN) based computer aided detection (CADe) of lesions in …

Background: Recently the American Society for Gastrointestinal Endoscopy addressed the
'resect and discard'strategy, determining that accurate in vivo differentiation of colorectal …

Background & Aims Precise optical diagnosis of colorectal polyps could improve the cost-
effectiveness of colonoscopy and reduce polypectomy-related complications. However, it is …

Background The use of artificial intelligence (AI) in detecting colorectal neoplasia during
colonoscopy holds the potential to enhance adenoma detection rates (ADRs) and reduce …

Background Computer-aided detection (CADe) increases adenoma detection in primary
screening colonoscopy. The potential benefit of CADe in a fecal immunochemical test (FIT) …

The adenoma detection rate is an established quality indicator for colonoscopy. For
instance, a 1% increase in the adenoma detection rate was associated with a 3% decrease …

Objective This study was performed to evaluate whether the use of CAD EYE (Fujifilm,
Tokyo, Japan) for colonoscopy improves colonoscopy quality in gastroenterology trainees …

Background and Aims Up to 30% of adenomas might be missed during screening
colonoscopy—these could be polyps that appear on-screen but are not recognized by …

Background Artificial intelligence systems have been developed to improve polyp detection.
We aimed to evaluate the effect of real-time computer-aided detection (CADe) on the …