The use of machine learning in the study of suicidal and non-suicidal self-injurious thoughts and behaviors: A systematic review.

Journal: Journal of affective disorders
PMID: 30699872

Abstract

BACKGROUND: Machine learning techniques offer promise to improve suicide risk prediction. In the current systematic review, we aimed to review the existing literature on the application of machine learning techniques to predict self-injurious thoughts and behaviors (SITBs).

Authors

  • Taylor A Burke
    Temple University, Department of Psychology, Philadelphia, PA, USA. Electronic address: taylor.burke@temple.edu.
  • Brooke A Ammerman
    University of Notre Dame, Department of Psychology, Notre Dame, IN, USA.
  • Ross Jacobucci
    University of Notre Dame, Department of Psychology, Notre Dame, IN, USA.

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