Background Multiple computer-aided systems for polyp detection (CADe) have been
introduced into clinical practice, with an unclear effect on examiner behavior. This study …

Abstract Introduction: Computer-aided detection (CADe) helps increase colonoscopic polyp
detection. However, little is known about other performance metrics like the number and …

Background and aims Computer-aided polyp detection (CADe) may become a standard for
polyp detection during colonoscopy. Several systems are already commercially available …

Background and Study Aims Small polyps are occasionally missed during colonoscopy. This
study was conducted to validate the diagnostic performance of a polyp‐detection algorithm …

Background and Aims Computer-aided detection (CADe) has been shown to improve polyp
detection in clinical trials. Limited data exist on the impact, utilization, and attitudes toward …

Background The occurrence of false-positive alerts is an important outcome measure in
computer-aided colon polyp detection (CADe) studies. However, there is no consensus …

Background The efficiency of artificial intelligence as computer‐aided detection (CADe)
systems for colorectal polyps has been demonstrated in several randomized trials. However …

Artificial intelligence (AI) has increasingly been employed in multiple fields, and there has
been significant interest in its use within gastrointestinal endoscopy. Computer-aided …

METHODS: Between September 28, 2020, and September 24, 2021, a randomized
controlled trial (AI-SEE) was performed evaluating the impact of CADe on polyp detection in …

Background and study aims Artificial intelligence (AI)-based systems for computer-aided
detection (CADe) of polyps receive regular updates and occasionally offer customizable …