Development of CSOARG: a single-cell and multi-omics-based machine learning model for ovarian cancer prognosis and drug response prediction.

Journal: Frontiers in oncology
Published Date:

Abstract

OBJECTIVE: Ovarian cancer is the most deadly gynaecological malignancy. This study aims to generate a predictive model for prognosis and therapeutic responses in ovarian cancer using defined specific genes.

Authors

  • Junyu Chen
    Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, 21287, USA.
  • Bin Guan
    School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, 230009, China.
  • Jihong Zhang
    Research Center for Clinical Medicine, Jinshan Hospital, Fudan University, Shanghai, China.
  • Xin Li
    Veterinary Diagnostic Center, Shanghai Animal Disease Control Center, Shanghai, China.
  • Jingyi Fang
    Research Center for Clinical Medicine, Jinshan Hospital, Fudan University, Shanghai, China.
  • Wencai Guan
    Research Center for Clinical Medicine, Jinshan Hospital, Fudan University, Shanghai, China.
  • Qi Lu
    Key Laboratory for Optoelectronic Technology and System of the Education Ministry of China, College of Optoelectronic Engineering, Chongqing University, Chongqing, China.
  • Guoxiong Xu
    Research Center for Clinical Medicine, Jinshan Hospital, Fudan University, Shanghai, China.

Keywords

No keywords available for this article.