Do no harm: a roadmap for responsible machine learning for health care.

Journal: Nature medicine
Published Date: Aug 19, 2019

Abstract

Interest in machine-learning applications within medicine has been growing, but few studies have progressed to deployment in patient care. We present a framework, context and ultimately guidelines for accelerating the translation of machine-learning-based interventions in health care. To be successful, translation will require a team of engaged stakeholders and a systematic process from beginning (problem formulation) to end (widespread deployment).

Authors

  • Jenna Wiens
    Computer Science and Engineering, University of Michigan, Ann Arbor.
  • Suchi Saria
    Department of Computer Science, Johns Hopkins University, Baltimore, MD.
  • Mark Sendak
    Duke Institute for Health Innovation.
  • Marzyeh Ghassemi
    Electrical Engineering and Computer Science, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States.
  • Vincent X Liu
    3 Division of Research, Kaiser Permanente, Oakland, California.
  • Finale Doshi-Velez
    School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.
  • Kenneth Jung
    Program in Biomedical Informatics, Stanford University, Stanford, California, USA.
  • Katherine Heller
    Department of Statistical Sciences.
  • David Kale
    Information Sciences Institute, University of Southern California, Los Angeles, CA, USA.
  • Mohammed Saeed
    Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan.
  • Pilar N Ossorio
    Law School, University of Wisconsin-Madison, Madison, WI, USA.
  • Sonoo Thadaney-Israni
    Presence and Program in Bedside Medicine, Stanford University School of Medicine, Stanford, CA, USA.
  • Anna Goldenberg
    SickKids Research Institute, 686 Bay Street, Toronto, ON M5G 0A4, Canada; Department of Computer Science, University of Toronto, 40 St. George Street, Toronto, ON M5S 2E4, Canada. Electronic address: anna.goldenberg@utoronto.ca.

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