Importance Despite the potential of machine learning to improve multiple aspects of patient
care, barriers to clinical adoption remain. Randomized clinical trials (RCTs) are often a …

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

Background & Aims Artificial intelligence-based computer-aided polyp detection (CADe)
systems are intended to address the issue of missed polyps during colonoscopy. The effect …

Background The number of artificial intelligence (AI) studies in medicine has exponentially
increased recently. However, there is no clear quantification of the clinical benefits of …

Abstract The Consolidated Standards of Reporting Trials extension for Artificial Intelligence
interventions (CONSORT-AI) was published in September 2020. Since its publication …

Background Artificial intelligence systems have been developed to improve polyp detection.
We aimed to evaluate the effect of real-time computer-aided detection (CADe) on the …

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

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 and Aims Artificial intelligence–based computer-aid detection (CADe) devices
have been recently tested in colonoscopies, increasing the adenoma detection rate (ADR) …

Background: Randomized clinical trials (RCTs) of computer-aided detection (CADe) system–
enhanced colonoscopy compared with conventional colonoscopy suggest increased …