Developing Acute Event Risk Profiles for Older Adults with Dementia in Long-Term Care Using Motor Behavior Clusters Derived from Deep Learning.

Journal: Journal of the American Medical Directors Association
Published Date: May 17, 2022

Abstract

OBJECTIVES: This paper uses deep (machine) learning techniques to develop and test how motor behaviors, derived from location and movement sensor tracking data, may be associated with falls, delirium, and urinary tract infections (UTIs) in long-term care (LTC) residents.

Authors

  • Ramin Ramazi
    Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA. Electronic address: ramazi@udel.edu.
  • Mary Elizabeth Libbey Bowen
    School of Nursing, University of Delaware, Newark, DE, USA; Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA; Coatesville Veterans Affairs Medical Center, Coatesville, PA, USA.
  • Aidan J Flynn
    Coatesville Veterans Affairs Medical Center, Coatesville, PA, USA.
  • Rahmatollah Beheshti
    University of Delaware.

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