Identification of suicidal behavior among psychiatrically hospitalized adolescents using natural language processing and machine learning of electronic health records.

Journal: PloS one
PMID: 30779800

Abstract

OBJECTIVE: The rapid proliferation of machine learning research using electronic health records to classify healthcare outcomes offers an opportunity to address the pressing public health problem of adolescent suicidal behavior. We describe the development and evaluation of a machine learning algorithm using natural language processing of electronic health records to identify suicidal behavior among psychiatrically hospitalized adolescents.

Authors

  • Nicholas J Carson
    Health Equity Research Lab, Cambridge Health Alliance, Cambridge, MA, United States of America.
  • Brian Mullin
    Health Equity Research Laboratory, Cambridge Health Alliance, Department of Psychiatry, Harvard Medical School, 1035 Cambridge Street, Suite 26, Cambridge, MA 02141, USA.
  • Maria Jose Sanchez
    Health Equity Research Lab, Cambridge Health Alliance, Cambridge, MA, United States of America.
  • Frederick Lu
    Health Equity Research Lab, Cambridge Health Alliance, Cambridge, MA, United States of America.
  • Kelly Yang
    Health Equity Research Lab, Cambridge Health Alliance, Cambridge, MA, United States of America.
  • Michelle Menezes
    Health Equity Research Lab, Cambridge Health Alliance, Cambridge, MA, United States of America.
  • Benjamin Lê Cook
    Health Equity Research Lab, Cambridge Health Alliance, Cambridge, MA, United States of America.

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