A deep-learning model using enhanced chest CT images to predict PD-L1 expression in non-small-cell lung cancer patients.

Journal: Clinical radiology
Published Date: Oct 1, 2023

Abstract

AIM: To develop a deep-learning model using contrast-enhanced chest computed tomography (CT) images to predict programmed death-ligand 1 (PD-L1) expression in patients with non-small-cell lung cancer (NSCLC).

Authors

  • P M Liu
    Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
  • B Feng
    School of Electronic Information and Automation, Guilin University of Aerospace Technology, Guilin, Guangxi, 541004, China.
  • J F Shi
    School of Electronic Information and Automation, Guilin University of Aerospace Technology, Guilin, Guangxi, 541004, China.
  • H J Feng
    Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
  • Z J Hu
    School of Electronic Information and Automation, Guilin University of Aerospace Technology, Guilin, Guangxi, 541004, China.
  • Y H Chen
    School of Electronic Information and Automation, Guilin University of Aerospace Technology, Guilin, Guangxi, 541004, China.
  • J P Zhang
    Cancer Center, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Third Hospital of Shanxi Medical University, Taiyuan, 030032, China; Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China. Electronic address: junpingzhang-118@163.com.

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