Stratification of gastric cancer risk using a deep neural network

Stratification of gastric cancer risk using a deep neural network

Background and Aim Stratifying gastric cancer (GC) risk and endoscopy findings in high‐risk individuals may provide effective surveillance for GC. We developed a computerized image‐ analysis system for endoscopic images to stratify the risk of GC. Methods The system was trained using images taken du...

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Bibliographic Details
Main Authors: Hiroko Nakahira, Ryu Ishihara, Kazuharu Aoyama, Mitsuhiro Kono, Hiromu Fukuda, Yusaku Shimamoto, Kentaro Nakagawa, Masayasu Ohmori, Taro Iwatsubo, Hiroyoshi Iwagami, Kenshi Matsuno, Shuntaro Inoue, Noriko Matsuura, Satoki Shichijo, Akira Maekawa, Takashi Kanesaka, Sachiko Yamamoto, Yoji Takeuchi, Koji Higashino, Noriya Uedo, Takashi Matsunaga, Tomohiro Tada
Format: Article
Language:English
Published: Wiley 2020-06-01
Series:JGH Open
Subjects:
artificial intelligence
convolutional neural network
endoscopy
gastric cancer
Online Access:https://doi.org/10.1002/jgh3.12281

Internet

https://doi.org/10.1002/jgh3.12281

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