Purpose To assess the diagnostic performance of distributed human intelligence for the
classification of polyp candidates identified with computer-aided detection (CAD) for …

The early endoscopic identification, resection, and treatment of precancerous adenoma and
early-stage cancer has been shown to reduce not only the prevalence of colorectal cancer …

Background and Aims Endoscopic treatment is recommended for low-grade dysplasia
(LGD), high-grade dysplasia (HGD), and colorectal cancer (CRC) with submucosal (SM) …

Background Endocytoscopy enables in vivo observation of nuclei at 450× magnification
during GI endoscopy, thus allowing precise prediction of lesion pathology. However …

Background Upper gastrointestinal cancers (including oesophageal cancer and gastric
cancer) are the most common cancers worldwide. Artificial intelligence platforms using deep …

Computer-aided diagnosis offers a promising solution to reduce variation in colonoscopy
performance. Pooled miss rates for polyps are as high as 22%, and associated interval …

Background & Aims Both computer-aided detection (CADe)-assisted and Endocuff-assisted
colonoscopy have been found to increase adenoma detection. We investigated the …

Abstract Background & Aims Colonoscopy for colorectal cancer screening is endoscopist
dependent, and colonoscopy quality improvement programs aim to improve efficacy. This …

Background and aims Artificial intelligence has been shown to increase adenoma detection
rate (ADR) as the main surrogate outcome parameter of colonoscopy quality. To which …

Background Endoscopic resection (ER) is widely applied to treat early colorectal cancer
(CRC). Predicting the invasion depth of early CRC is critical in determining treatment …