A deep learning- and CT image-based prognostic model for the prediction of survival in non-small cell lung cancer.

Journal: Medical physics
Published Date: Oct 28, 2021

Abstract

OBJECTIVE: To assist clinicians in arranging personalized treatment, planning follow-up programs and extending survival times for non-small cell lung cancer (NSCLC) patients, a method of deep learning combined with computed tomography (CT) imaging for survival prediction was designed.

Authors

  • Wen Chen
    School of Cyber Science and Engineering, Sichuan University, Chengdu, Sichuan, China.
  • Xuewen Hou
    School of Medical Imaging, Shanghai University of Medicine & Health Science, Shanghai, China.
  • Ying Hu
    Department of Ultrasonography, The First Affiliated Hospital, College of Medicine, Zhejiang University, Qingchun Road No. 79, Hangzhou, Zhejiang 310003, China.
  • Gang Huang
    School of Health, Shanghai University of Medicine & Health Sciences, Shanghai 201318, China.
  • Xiaodan Ye
    Department of Radiology, Shanghai Chest Hospital Shanghai Jiao Tong University, 200030, Shanghai, PR China. Electronic address: yuanyxd@163.com.
  • Shengdong Nie
    School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, 516 Jun Gong Road, Shanghai, 200093, China.

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