Automated machine learning: Review of the state-of-the-art and opportunities for healthcare.

Journal: Artificial intelligence in medicine
Published Date: Feb 21, 2020

Abstract

OBJECTIVE: This work aims to provide a review of the existing literature in the field of automated machine learning (AutoML) to help healthcare professionals better utilize machine learning models "off-the-shelf" with limited data science expertise. We also identify the potential opportunities and barriers to using AutoML in healthcare, as well as existing applications of AutoML in healthcare.

Authors

  • Jonathan Waring
    Dana-Farber Cancer Institute, Department of Informatics & Analytics, Boston, MA, 02215, United States; Harvard T.H. Chan School of Public Health, Department of Biostatistics, Boston, MA, 02215, United States. Electronic address: jonathan_waring@dfci.harvard.edu.
  • Charlotta Lindvall
    Harvard Medical School, Boston, MA.
  • Renato Umeton
    Dana-Farber Cancer Institute, Boston, MA, USA.

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