The Efficacy of AI-Assisted CADe Systems in Colorectal Polyps and Adenomas during Colonoscopies: A Systematic Review

Colorectal polyps and adenomas are a significant health concern that can lead to colorectal cancer. Detecting early is important remove them in timely manner, reducing the risk of Artificial intelligence (AI) could assist identifying more efficiently. This study will investigate potential benefits AI technology detecting adenomas, using AI-assisted colonoscopy diagnostic systems. The goal determine if there differences detection rates compared standard methods. PRISMA Statement 2020 guidelines were adhered this systematic review. Three databases searched including PubMed/MEDLINE, Embase Web Science through February 23, 2023. A combination following keywords was used: AI, Artificial, Intelligence, Colorectal, Polyp, Adenoma. adenoma rate (ADR) polyp (PDR) additionally meta-analyzed for proportions, reported as odds ratio (OR), applying 95% confidence intervals (CI). total 9 randomized clinical trials included review, pooling 6981 participants. findings presented systematically, based on design, used, effects ADR PDR, key conclusions. meta-analytical follows. On random-effects model, (OR) 1.532 (95% CI=1.125-2.087), with favoring CADe systems (P=0.0068). Similarly, when assessing chance diagnosing an add-on alone, 1.893 CI=1.687-2.125, P<0.0001). review found real-time computer-aided during improved polyps. use system feasible safe, future studies should focus improving quality indicators most widely used– ADR. Larger controlled needed evaluate impact serrated its effect endoscopists lower rates.