Application of Artificial Intelligence for Preoperative Diagnostic and Prognostic Prediction in Epithelial Ovarian Cancer Based on Blood Biomarkers.

Journal: Clinical cancer research : an official journal of the American Association for Cancer Research
Published Date: May 15, 2019

Abstract

PURPOSE: We aimed to develop an ovarian cancer-specific predictive framework for clinical stage, histotype, residual tumor burden, and prognosis using machine learning methods based on multiple biomarkers.

Authors

  • Eiryo Kawakami
    Medical Sciences Innovation Hub Program, RIKEN, Yokohama, Kanagawa, Japan.
  • Junya Tabata
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Nozomu Yanaihara
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan. yanazou@jikei.ac.jp.
  • Tetsuo Ishikawa
    Medical Sciences Innovation Hub Program, RIKEN, Yokohama, Kanagawa, Japan.
  • Keita Koseki
    Medical Sciences Innovation Hub Program, RIKEN, Yokohama, Kanagawa, Japan.
  • Yasushi Iida
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Misato Saito
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Hiromi Komazaki
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Jason S Shapiro
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Chihiro Goto
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Yuka Akiyama
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Ryosuke Saito
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Motoaki Saito
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Hirokuni Takano
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Kyosuke Yamada
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.
  • Aikou Okamoto
    Department of Obstetrics and Gynecology, The Jikei University School of Medicine, Minato-ku, Tokyo, Japan.

Keywords

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