Computer-aided diagnosis for colonoscopy

With recent breakthroughs in artificial intelligence, computeraided diagnosis (CAD) for colonoscopy is gaining increasing attention. CAD allows automated detection and classification (i. e. pathological prediction) of colorectal polyps during realtime endoscopy, potentially helping endoscopists to avoid missing and mischaracterizing polyps. Although the evidence has not caught up with technological progress, CAD has the potential to improve the quality of colonoscopy, with some CAD systems for polyp classification achieving diagnostic performance exceeding the threshold required for optical biopsy. The present article provides an overview of this topic from the perspective of endoscopists, with a particular focus on evidence, limitations, and clinical applications.