Development of a real-time endoscopic image diagnosis support system using deep learning technology in colonoscopy.

ABSTRACT: Gaps in colonoscopy skills among endoscopists, primarily due to experience, have been identified, and solutions are critically needed. Hence, the development of a real-time robust detection system for colorectal neoplasms is considered to significantly reduce the risk of missed lesions during colonoscopy. Here, we develop an artificial intelligence (AI) system that automatically detects early signs of colorectal cancer during colonoscopy; the AI system shows the sensitivity and specificity are 97.3% (95% confidence interval [CI] = 95.9%-98.4%) and 99.0% (95% CI = 98.6%-99.2%), respectively, and the area under the curve is 0.975 (95% CI = 0.964-0.986) in the validation set. Moreover, the sensitivities are 98.0% (95% CI = 96.6%-98.8%) in the polypoid subgroup and 93.7% (95% CI = 87.6%-96.9%)

SUBMITTER: Yamada M 

PROVIDER: S-EPMC6783454 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature