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

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

Objectives: Multiple meta-analyses which investigated the comparative efficacy and safety of
artificial intelligence (AI)-aid colonoscopy (AIC) vs. conventional colonoscopy (CC) in the …

Colonoscopy is an important method to diagnose polyps, especially adenomatous polyps.
However, the rate of missed diagnoses is relatively high. In this study, we aimed to …

Background and aims Improving the rate of polyp detection is an important measure to
prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through …

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

Background Artificial intelligence (AI) assistance has been considered as a promising way to
improve colonoscopic polyp detection, but there are limited prospective studies on real‐time …

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 Colonoscopy reduces the incidence of colorectal cancer (CRC) by allowing
detection and resection of neoplastic polyps. Evidence shows that many small polyps are …

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