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  1. Article

    Open Access

    Cooperation between artificial intelligence and endoscopists for diagnosing invasion depth of early gastric cancer

    The diagnostic ability of endoscopists to determine invasion depth of early gastric cancer is not favorable. We designed an artificial intelligence (AI) classifier for differentiating intramucosal and submucos...

    Atsushi Goto, Naoto Kubota, Jun Nishikawa, Ryo Ogawa, Koichi Hamabe in Gastric Cancer (2023)

  2. Article

    Open Access

    Objective Assessment of the Utility of Chromoendoscopy with a Support Vector Machine

    The utility of chromoendoscopy for early gastric cancer (GC) was determined by machine learning using data of color differences.

    Ryo Ogawa, Jun Nishikawa, Eizaburo Hideura in Journal of Gastrointestinal Cancer (2019)