Background: The role of computer-aided detection in identifying advanced colorectal
neoplasia is unknown. Objective: To evaluate the contribution of computer-aided detection …

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 …

Colorectal cancer remains a leading cause of morbidity and mortality in the United States.
Advances in artificial intelligence (AI), specifically computer aided detection and computer …

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

Simple Summary There has been an exponential rise in the availability of artificial
intelligence systems in endoscopy in recent years. As a result, maintaining an informed …

Background & Aims One-fourth of colorectal neoplasias are missed during screening
colonoscopies; these can develop into colorectal cancer (CRC). Deep learning systems …

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 computer-aided detection (CADe) of colorectal neoplasia
during colonoscopy may increase adenoma detection rates (ADRs) and reduce adenoma …

Background: Computer-aided diagnosis (CAD) for colonoscopy may help endoscopists
distinguish neoplastic polyps (adenomas) requiring resection from nonneoplastic polyps not …