Background and aims Improving the rate of polyp detection is an important measure to
prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through …

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 …

Background: Colonoscopy is the gold standard for polyp detection, but polyps may be
missed. Artificial intelligence (AI) technologies may assist in polyp detection. To date, most …

Background: This study aimed to compare artificial intelligence (AI)-aided colonoscopy with
conventional colonoscopy for polyp detection. Methods: A systematic literature search was …

Background Artificial intelligence (AI)-based polyp detection systems are used during
colonoscopy with the aim of increasing lesion detection and improving colonoscopy quality …

The detection and removal of precancerous polyps via colonoscopy is the gold standard for
the prevention of colon cancer. However, the detection rate of adenomatous polyps can vary …

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

Objective The effect of colonoscopy on colorectal cancer mortality is limited by several
factors, among them a certain miss rate, leading to limited adenoma detection rates (ADRs) …

Background Colonoscopy reduces the incidence of colorectal cancer (CRC) by allowing
detection and resection of neoplastic polyps. Evidence shows that many small polyps are …

We developed and validated a deep-learning algorithm for polyp detection. We used a
YOLOv2 to develop the algorithm for automatic polyp detection on 8,075 images (503 …