Convolutional neural network models for cancer type prediction based on gene expression.

Journal: BMC medical genomics
Published Date:

Abstract

BACKGROUND: Precise prediction of cancer types is vital for cancer diagnosis and therapy. Through a predictive model, important cancer marker genes can be inferred. Several studies have attempted to build machine learning models for this task however none has taken into consideration the effects of tissue of origin that can potentially bias the identification of cancer markers.

Authors

  • Milad Mostavi
  • Yu-Chiao Chiu
    Greehey Children's Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA.
  • Yufei Huang
    Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, TX, 78249, USA.
  • Yidong Chen
    Greehey Children's Cancer Research Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, 78229, USA. ChenY8@uthscsa.edu.