Deep learning predicts epidermal growth factor receptor mutation subtypes in lung adenocarcinoma.

Journal: Medical physics
Published Date: Nov 7, 2021

Abstract

PURPOSE: This study aimed to explore the predictive ability of deep learning (DL) for the common epidermal growth factor receptor (EGFR) mutation subtypes in patients with lung adenocarcinoma.

Authors

  • Jiangdian Song
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Liaoning, Shenyang, 110819, China.
  • Changwei Ding
    Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, China.
  • Qinlai Huang
    School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
  • Ting Luo
    Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Key Laboratory of Artificial Intelligence, Kunming University of Science and Technology, Kunming, 650500, China. Electronic address: luoting@stu.kust.edu.cn.
  • Xiaoman Xu
    School of pharmacy, Nanjing medical university, Nanjing, Jiangsu, 211166, People's Republic of China.
  • Zongjian Chen
    School of Medical Informatics, China Medical University, Shenyang, China.
  • Shu Li
    China Medical University College of Health Management, Shenyang 110122, Liaoning Province, China.

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