Background and study aims With the advent of deep neural networks (DNN) learning, the
field of artificial intelligence (AI) is rapidly evolving. Recent randomized controlled trials …

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

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

Abstract Background and Aim The utility of artificial intelligence (AI) in colonoscopy has
gained popularity in current times. Recent trials have evaluated the efficacy of deep …

Background and Aims One-fourth of colorectal neoplasia are missed at screening
colonoscopy, representing the main cause of interval colorectal cancer. Deep learning …

Methods: A comprehensive literature search of PubMed/Medline, Embase, and Cochrane
was performed through May 6, 2022, to include RCTs comparing ADR for any endoscopic …

Goals and background Studies analyzing artificial intelligence (AI) in colonoscopies have
reported improvements in detecting colorectal cancer (CRC) lesions, however its utility in the …

Background Artificial intelligence (AI)-based polyp detection systems are used during
colonoscopy with the aim of increasing lesion detection and improving colonoscopy quality …

Background Adenoma detection rate (ADR) varies significantly between endoscopists, with
adenoma miss rates (AMRs) up to 26%. Artificial intelligence (AI) systems may improve …

Background: This study aimed to compare artificial intelligence (AI)-aided colonoscopy with
conventional colonoscopy for polyp detection. Methods: A systematic literature search was …