Prediction of prognosis and treatment response in ovarian cancer patients from histopathology images using graph deep learning: a multicenter retrospective study.

Journal: European journal of cancer (Oxford, England : 1990)
Published Date: Jan 13, 2024

Abstract

BACKGROUND: Ovarian cancer (OV) is a prevalent and deadly disease with high mortality rates. The development of accurate prognostic tools and personalized therapeutic strategies is crucial for improving patient outcomes.

Authors

  • Zijian Yang
    Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Yibo Zhang
    Electrical and Computer Engineering Department, University of California, Los Angeles, CA 90095, USA.
  • Lili Zhuo
    School of Biomedical Engineering, Wenzhou Medical University, Wenzhou 325027, PR China.
  • Kaidi Sun
    Department of Gynecology, Harbin Medical University Cancer Hospital, Harbin 150081, PR China.
  • Fanling Meng
    Department of Gynecology, Harbin Medical University Cancer Hospital, Harbin 150081, PR China. Electronic address: mflzlyy_edu@163.com.
  • Meng Zhou
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, People's Republic of China. biofomeng@hotmail.com.
  • Jie Sun
    College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, People's Republic of China.

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