Accelerated training of bootstrap aggregation-based deep information extraction systems from cancer pathology reports.

Journal: Journal of biomedical informatics
Published Date: Sep 9, 2020

Abstract

OBJECTIVE: In machine learning, it is evident that the classification of the task performance increases if bootstrap aggregation (bagging) is applied. However, the bagging of deep neural networks takes tremendous amounts of computational resources and training time. The research question that we aimed to answer in this research is whether we could achieve higher task performance scores and accelerate the training by dividing a problem into sub-problems.

Authors

  • Hong-Jun Yoon
  • Hilda B Klasky
    Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, United States of America. Electronic address: klaskyhb@ornl.gov.
  • John P Gounley
    Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, United States of America. Electronic address: gounleyjp@ornl.gov.
  • Mohammed Alawad
    Computational Sciences and Engineering Division, Health Data Sciences Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.
  • Shang Gao
    Department of Orthopedics, Orthopedic Center of Chinese PLA, Southwest Hospital, Third Military Medical University, Chongqing, 400038, P.R.China.
  • Eric B Durbin
    University of Kentucky, Lexington, KY.
  • Xiao-Cheng Wu
    Department of Epidemiology, Louisiana State University New Orleans School of Public Health, New Orleans, LA 70112, United States.
  • Antoinette Stroup
    New Jersey State Cancer Registry, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, 08901, United States of America. Electronic address: nan.stroup@rutgers.edu.
  • Jennifer Doherty
    Utah Cancer Registry, University of Utah School of Medicine, Salt Lake City, UT 84132, United States of America. Electronic address: Jen.Doherty@hci.utah.edu.
  • Linda Coyle
    Information Management Services Inc, Calverton, Maryland, USA.
  • Lynne Penberthy
    Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland, USA.
  • J Blair Christian
    Biomedical Sciences, Engineering, and Computing Group, Health Data Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
  • Georgia D Tourassi

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