Background and Aims The efficacy and safety of colonoscopy performed by artificial
intelligence (AI)-assisted novices remain unknown. The aim of this study was to compare the …

Background In colonoscopy screening for colorectal cancer, human vision limitations may
lead to higher miss rate of lesions; artificial intelligence (AI) assistance has been …

Background and study aims Adenoma detection rate (ADR) is a well-accepted quality
indicator of screening colonoscopy. In recent years, the added value of artificial intelligence …

Abstract Background & Aims Artificial intelligence (AI) may detect colorectal polyps that have
been missed due to perceptual pitfalls. By reducing such miss rate, AI may increase the …

Background and aims Artificial intelligence has been shown to increase adenoma detection
rate (ADR) as the main surrogate outcome parameter of colonoscopy quality. To which …

Background This meta-analysis aimed to determine whether artificial intelligence (AI)
improves colonoscopy outcome metrics ie adenoma detection rate (ADR) and polyp …

Background: Artificial intelligence (AI) could minimize the operator-dependent variation in
colonoscopy quality. Computer-aided detection (CADe) has improved adenoma detection …

Background Colonoscopies have long been the gold standard for detection of pre-malignant
neoplastic lesions of the colon. Our previous study tried real-time artificial intelligence (AI) …

Background Colonoscopy is a mainstay to detect premalignant neoplastic lesions in the
colon. Real-time Artificial Intelligence (AI)-aided colonoscopy purportedly improves the …

The performance of artificial intelligence-aided colonoscopy (AIAC) in a real-world setting
has not been described. We compared adenoma and polyp detection rates (ADR/PDR) in a …