1. Volume 154, Issue 8, Pages 2027-2029.e3 (June 2018)
Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience 
Masashi Misawa, Shin-ei Kudo, Yuichi Mori, Tomonari Cho, Shinichi Kataoka, Akihiro Yamauchi, Yushi Ogawa, Yasuharu Maeda, Kenichi Takeda, Katsuro Ichimasa, Hiroki Nakamura, Yusuke Yagawa, Naoya Toyoshima, Noriyuki Ogata, Toyoki Kudo, Tomokazu Hisayuki, Takemasa Hayashi, Kunihiko Wakamura, Toshiyuki Baba, Fumio Ishida, Hayato Itoh, Holger Roth, Masahiro Oda, Kensaku Mori 
Gastroenterology 
Volume 154, Issue 8, Pages e3 (June 2018)
DOI: /j.gastro
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2. Figure 1
The system presented the probability of the presence of polyps as a percentage in the upper left corner of the endoscopic image. When the probability exceeded the cutoff, the computer-aided detection (CADe) system warned of the possibility of the presence of polyps by changing the color in the 4 corners of the endoscopic image to red.
Gastroenterology  , e3DOI: ( /j.gastro )
Copyright © 2018 AGA Institute Terms and Conditions

3. Figure 2
Receiver operating characteristic (ROC) analysis for the system. The area under the curve was The red square plot indicates a probability of 0.15.
Gastroenterology  , e3DOI: ( /j.gastro )
Copyright © 2018 AGA Institute Terms and Conditions