Comparison of deep learning models to traditional Cox regression in predicting survival of colon cancer: Based on the SEER database.

Journal: Journal of gastroenterology and hepatology
Published Date: May 9, 2024

Abstract

BACKGROUND AND AIM: In this study, a deep learning algorithm was used to predict the survival rate of colon cancer (CC) patients, and compared its performance with traditional Cox regression.

Authors

  • Zihan Qu
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Yashan Wang
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Dingjie Guo
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Guangliang He
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Chuanying Sui
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Yuqing Duan
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Xin Zhang
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.
  • Hengyu Meng
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Linwei Lan
    Department of Epidemiology and Statistics, School of Public Health, Jilin University, Changchun, 130021, China.
  • Xin Liu
    Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences, Weifang, Shandong, China.

Keywords

External Resources

Popular Topics
Recent Journals