Machine learning-based radiomics strategy for prediction of cell proliferation in non-small cell lung cancer.

Journal: European journal of radiology
Published Date:

Abstract

PURPOSE: To explore the feasibility and performance of machine learning-based radiomics classifier to predict the cell proliferation(Ki-67)in non-small cell lung cancer (NSCLC).

Authors

  • Qianbiao Gu
    Department of Radiology, The Third Xiangya Hospital of Central South University, Changsha 410013, China; Department of Radiology, The People's Hospital of Hunan Province, The First Hospital Affiliated of Hunan Normal University, Changsha 410005, China.
  • Zhichao Feng
    Department of Radiology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China.
  • Qi Liang
    Department of Radiology, The Third Xiangya Hospital of Central South University, Changsha 410013, China.
  • Meijiao Li
    Department of Radiology, The Third Xiangya Hospital of Central South University, Changsha 410013, China.
  • Jiao Deng
    Department of Radiology, The Third Xiangya Hospital of Central South University, Changsha 410013, China.
  • Mengtian Ma
    Department of Radiology, The Third Xiangya Hospital of Central South University, Changsha 410013, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Jianbin Liu
    Department of Radiology, The People's Hospital of Hunan Province, The First Hospital Affiliated of Hunan Normal University, Changsha 410005, China.
  • Peng Liu
    Department of Clinical Pharmacy, Dazhou Central Hospital, Dazhou 635000, China.
  • Pengfei Rong
    Department of Radiology, The Third Xiangya Hospital, Central South University, Changsha, Hunan, 410013, China.