Reproducible Machine Learning Methods for Lung Cancer Detection Using Computed Tomography Images: Algorithm Development and Validation.

Journal: Journal of medical Internet research
Published Date: Aug 5, 2020

Abstract

BACKGROUND: Chest computed tomography (CT) is crucial for the detection of lung cancer, and many automated CT evaluation methods have been proposed. Due to the divergent software dependencies of the reported approaches, the developed methods are rarely compared or reproduced.

Authors

  • Kun-Hsing Yu
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
  • Tsung-Lu Michael Lee
    Department of Information Engineering, Kun Shan University, Tainan, Taiwan.
  • Ming-Hsuan Yen
    Graduate Program of Multimedia Systems and Intelligent Computing, National Cheng Kung University and Academia Sinica, Tainan, Taiwan.
  • S C Kou
    Department of Statistics, Harvard University, Cambridge, MA, United States.
  • Bruce Rosen
    Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
  • Jung-Hsien Chiang
    Department of Computer Science and Information Engineering, National Cheng Kung University, 1, University Road, Tainan City, Taiwan.
  • Isaac S Kohane
    Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. Isaac_Kohane@hms.harvard.edu.

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