Background and Aims We performed a meta-analysis of all published studies to determine
the diagnostic accuracy of artificial intelligence (AI) on histology prediction and detection of …

Background Artificial intelligence (AI) is used to solve the problem of missed diagnosis of
polyps in colonoscopy, which has been proved to improve the detection rate of adenomas …

We aimed to develop a computer-aided diagnostic system (CAD) for predicting colorectal
polyp histology using deep-learning technology and to validate its performance. Near-focus …

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

Background and Aims One-fourth of colorectal neoplasia are missed at screening
colonoscopy, representing the main cause of interval colorectal cancer. Deep learning …

Artificial intelligence (AI) presents a novel platform for improving disease diagnosis.
However, the clinical utility of AI remains limited to discovery studies, with poor translation to …

Background & Aims Narrow-band imaging (NBI) can be used to determine whether
colorectal polyps are adenomatous or hyperplastic. We investigated whether an artificial …

Background In general, academic but not community endoscopists have demonstrated
adequate endoscopic differentiation accuracy to make the 'resect and discard'paradigm for …

Research in computer-aided diagnosis (CAD) and the application of artificial intelligence
(AI) in the endoscopic evaluation of the gastrointestinal tract is novel. Since colonoscopy …

Objective The main aim of this study was to analyze the performance of different artificial
intelligence (AI) models in endoscopic colonic polyp detection and classification and …