Predictive models for patients with lung carcinomas to identify EGFR mutation status via an artificial neural network based on multiple clinical information.

Journal: Journal of cancer research and clinical oncology
Published Date: Mar 1, 2020

Abstract

PURPOSE: Epidermal growth factor receptor (EGFR) mutation testing has several limitations. Therefore, we built predictive models to determine the EGFR mutation status of patients and guide therapeutic decision-making.

Authors

  • Xiaoyi Qin
    Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
  • Hailong Wang
    Wenzhou Medical University, Wenzhou, Zhejiang, China.
  • Xiang Hu
    Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute Shanghai 200233, China.
  • Xiaolong Gu
    Department of Pneumology, Ningbo Yinzhou NO.2 Hospital, Ningbo, Zhejiang, China.
  • Wei Zhou
    Department of Eye Function Laboratory, Eye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

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