Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47084, first published .
Assessing Detection of Children With Suicide-Related Emergencies: Evaluation and Development of Computable Phenotyping Approaches

Assessing Detection of Children With Suicide-Related Emergencies: Evaluation and Development of Computable Phenotyping Approaches

Assessing Detection of Children With Suicide-Related Emergencies: Evaluation and Development of Computable Phenotyping Approaches

Juliet Beni Edgcomb   1, 2 , MD, PhD ;   Chi-hong Tseng   3 , PhD ;   Mengtong Pan   3 , BA, BS ;   Alexandra Klomhaus   3 , PhD ;   Bonnie T Zima   1, 2 , MPH, MD

1 Mental Health Informatics and Data Science (MINDS) Hub, Center for Community Health, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA, United States

2 Department of Psychiatry, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States

3 Department of Medicine Statistics Core, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States

Corresponding Author:

  • Juliet Beni Edgcomb, MD, PhD
  • Mental Health Informatics and Data Science (MINDS) Hub, Center for Community Health
  • Semel Institute for Neuroscience and Human Behavior
  • University of California Los Angeles
  • 760 Westwood Plaza
  • Los Angeles, CA, 90095
  • United States
  • Phone: 1 310 794-8278
  • Email: jedgcomb@mednet.ucla.edu