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Artificial Intelligence-assisted System Improves Endoscopic Identification of Colorectal Neoplasms
Shin-ei Kudo ,
Masashi Misawa ,
Yuichi Mori ,
Kinichi Hotta ,
Kazuo Ohtsuka ,
Hiroaki Ikematsu ,
Yutaka Saito ,
Kenichi Takeda ,
Hiroki Nakamura ,
Katsuro Ichimasa ,
Tomoyuki Ishigaki ,
Naoya Toyoshima ,
Toyoki Kudo ,
Takemasa Hayashi ,
Kunihiko Wakamura ,
Toshiyuki Baba ,
Ishida Fumio ,
Haruhiro Inoue ,
Hayato Itoh ,
Masahiro Oda ,
Kensaku Mori
September 2019
September 2019
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Abstract
Precise optical diagnosis of colorectal polyps could improve the cost-effectiveness
of colonoscopy and reduce polypectomy-related complications. However, it is difficult
for community-based non-experts to obtain sufficient diagnostic performance. Artificial
intelligence-based systems have been developed to analyze endoscopic images; they
identify neoplasms with high accuracy and low interobserver variation. We performed
a multi-center study to determine the diagnostic accuracy of EndoBRAIN, an artificial
intelligence-based system that analyzes cell nuclei, crypt structure, and microvessels
in endoscopic images, in identification of colon neoplasms.