Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 32374378

Abstract

OBJECTIVE: The goal of this study was to explore whether features of recorded and transcribed audio communication data extracted by machine learning algorithms can be used to train a classifier for anxiety.

Authors

  • George Demiris
    Department of Biobehavioral Health Sciences, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
  • Kristin L Corey Magan
    School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
  • Debra Parker Oliver
    Family Medicine, School of Medicine, University of Missouri, Columbia, Missouri, USA.
  • Karla T Washington
    2 Department of Family and Community Medicine, University of Missouri, Columbia, MO, USA.
  • Chad Chadwick
    Live Circle Inc, Ridgewood, New Jersey, USA.
  • Jeffrey D Voigt
    Live Circle Inc, Ridgewood, New Jersey, USA.
  • Sam Brotherton
    Live Circle Inc, Ridgewood, New Jersey, USA.
  • Mary D Naylor
    School of Nursing, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

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