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

Juliet Beni EdgcombChi-Hong TsengMengtong PanAlexandra M KlomhausBonnie T Zima
Published in: JMIR mental health (2023)
The capacity to detect children with SITB may be strengthened by applying a machine learning-based approach to codified health record data. To improve integration between clinical research informatics and child mental health care, future research is needed to evaluate the potential benefits of implementing detection approaches at the point of care and identifying precise targets for suicide prevention interventions in children.
Keyphrases
  • machine learning
  • young adults
  • mental health
  • public health
  • physical activity
  • artificial intelligence
  • label free
  • human health
  • deep learning
  • health information
  • drug induced
  • data analysis
  • clinical evaluation