The utility of artificial intelligence in suicide risk prediction and the management of suicidal behaviors.

Journal: The Australian and New Zealand journal of psychiatry
Published Date:

Abstract

OBJECTIVE: Suicide is a growing public health concern with a global prevalence of approximately 800,000 deaths per year. The current process of evaluating suicide risk is highly subjective, which can limit the efficacy and accuracy of prediction efforts. Consequently, suicide detection strategies are shifting toward artificial intelligence platforms that can identify patterns within 'big data' to generate risk algorithms that can determine the effects of risk (and protective) factors on suicide outcomes, predict suicide outbreaks and identify at-risk individuals or populations. In this review, we summarize the role of artificial intelligence in optimizing suicide risk prediction and behavior management.

Authors

  • Trehani M Fonseka
    Centre for Mental Health and Krembil Research Centre, University Health Network, Toronto, ON, Canada.
  • Venkat Bhat
    Centre for Mental Health and Krembil Research Centre, University Health Network, Toronto, ON, Canada.
  • Sidney H Kennedy
    Department of Psychiatry, University of Toronto, Toronto, ON, Canada.