The myth of generalisability in clinical research and machine learning in health care.

Journal: The Lancet. Digital health
Published Date: Aug 24, 2020

Abstract

An emphasis on overly broad notions of generalisability as it pertains to applications of machine learning in health care can overlook situations in which machine learning might provide clinical utility. We believe that this narrow focus on generalisability should be replaced with wider considerations for the ultimate goal of building machine learning systems that are useful at the bedside.

Authors

  • Joseph Futoma
    Department of Statistical Science, Duke University, Durham, North Carolina.
  • Morgan Simons
    Department of Medicine, NYU Langone Health, New York, NY, USA.
  • Trishan Panch
    Instructor, Department of Health Policy and Management, T.H. Chan School of Public Health, Harvard University, Boston, United States of America.
  • Finale Doshi-Velez
    School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.
  • Leo Anthony Celi
    Massachusetts Institute of Technology, Cambridge, MA, USA.

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