Machine Learning Enhances the Efficiency of Cognitive Screenings for Primary Care.

Journal: Journal of geriatric psychiatry and neurology
Published Date: Mar 17, 2019

Abstract

BACKGROUND: Incorporation of cognitive screening into the busy primary care will require the development of highly efficient screening tools. We report the convergence validity of a very brief, self-administered, computerized assessment protocol against one of the most extensively used, clinician-administered instruments-the Montreal Cognitive Assessment (MoCA).

Authors

  • Boaz Levy
    1 Department of Counseling and School Psychology, University of Massachusetts, Boston, MA, USA.
  • Courtney Hess
    1 Department of Counseling and School Psychology, University of Massachusetts, Boston, MA, USA.
  • Jacqueline Hogan
    1 Department of Counseling and School Psychology, University of Massachusetts, Boston, MA, USA.
  • Matthew Hogan
    2 McGraw-Hill Education, Boston, MA, USA.
  • James M Ellison
    3 Christiana Care Health System, Department of Psychiatry and Human Behavior, Sidney Kimmel Medical College, Thomas Jefferson University, DE, USA.
  • Sarah Greenspan
    1 Department of Counseling and School Psychology, University of Massachusetts, Boston, MA, USA.
  • Allison Elber
    1 Department of Counseling and School Psychology, University of Massachusetts, Boston, MA, USA.
  • Kathryn Falcon
    1 Department of Counseling and School Psychology, University of Massachusetts, Boston, MA, USA.
  • Daniel F Driscoll
    4 Tufts University School of Medicine, Boston, MA, USA.
  • Ardeshir Z Hashmi
    5 Cleveland Clinic, Lerner College of Medicine, Cleveland, OH, USA.

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