Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

Journal: JAMA psychiatry
PMID: 31642880

Abstract

IMPORTANCE: Suicide is a public health problem, with multiple causes that are poorly understood. The increased focus on combining health care data with machine-learning approaches in psychiatry may help advance the understanding of suicide risk.

Authors

  • Jaimie L Gradus
    Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts.
  • Anthony J Rosellini
    Department of Health Care Policy, Harvard Medical School.
  • Erzsébet Horváth-Puhó
    Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.
  • Amy E Street
    National Center for PTSD, VA Boston Healthcare System, and Department of Psychiatry, Boston University School of Medicine.
  • Isaac Galatzer-Levy
    Department of Psychiatry, New York University School of Medicine, New York.
  • Tammy Jiang
    Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts.
  • Timothy L Lash
    Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.
  • Henrik T Sørensen
    Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.

Keywords

External Resources

Popular Topics
Recent Journals