A deep learning risk prediction model for overall survival in patients with gastric cancer: A multicenter study.

Journal: Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Published Date: Jun 12, 2020

Abstract

BACKGROUND AND PURPOSE: Risk prediction of overall survival (OS) is crucial for gastric cancer (GC) patients to assess the treatment programs and may guide personalized medicine. A novel deep learning (DL) model was proposed to predict the risk for OS based on computed tomography (CT) images.

Authors

  • Liwen Zhang
    National Engineering Laboratory of Big Data Analytics, Xi'an Jiaotong University, Xi'an 710049, China.
  • Di Dong
    The Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.
  • Wenjuan Zhang
    Department of Biopharmaceutics, School of Pharmacy, Shenyang Pharmaceutical University, Wenhua Road, Shenyang 110016, China.
  • Xiaohan Hao
    Hefei National Lab for Physical Sciences at the Microscale and the Centers for Biomedical Engineering, University of Science and Technology of China, Hefei, Anhui, 230026, China.
  • Mengjie Fang
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; University of Chinese Academy of Sciences, Beijing, 100080, China.
  • Shuo Wang
    College of Tea & Food Science, Anhui Agricultural University, Hefei, China.
  • Wuchao Li
    Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, China.
  • Zaiyi Liu
    Department of Radiology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
  • Rongpin Wang
    Department of Radiology, Guizhou Provincial People's Hospital, Guiyang, 550002 China.
  • Junlin Zhou
    Department of Radiology, Lanzhou University Second Hospital, 730030 Lanzhou, Gansu, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

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