Machine learning for psychiatric patient triaging: an investigation of cascading classifiers.

Journal: Journal of the American Medical Informatics Association : JAMIA
Published Date: Nov 1, 2018

Abstract

OBJECTIVE: Develop an approach, One-class-at-a-time, for triaging psychiatric patients using machine learning on textual patient records. Our approach aims to automate the triaging process and reduce expert effort while providing high classification reliability.

Authors

  • Vivek Kumar Singh
    Information Systems and Decision Sciences, MUMA College of Business, University of South Florida, Tampa, Florida, USA.
  • Utkarsh Shrivastava
    Haworth College of Business, Department of Business Information Systems, Western Michigan University, Kalamazoo, Michigan, USA.
  • Lina Bouayad
    Center of Innovation on Disability and Rehabilitation Research, Department of Health Policy and Management, James A. Haley Veterans Hospital, and the University of South Florida College of Public Health, 8900 Grand Oak Circle, Tampa, FL, 33637, USA.
  • Balaji Padmanabhan
    Information Systems and Decision Sciences, MUMA College of Business, University of South Florida, Tampa, Florida, USA.
  • Anna Ialynytchev
    HSR&D Center of Innovation on Disability and Rehabilitation Research (CINDRR), James A. Haley Veterans Hospital, Tampa, Florida, USA.
  • Susan K Schultz
    James A. Haley Veterans Hospital, Geriatric Psychiatry, Tampa, Florida, USA.

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