Prediction models for high risk of suicide in Korean adolescents using machine learning techniques.

Journal: PloS one
Published Date: Jun 6, 2019

Abstract

OBJECTIVE: Suicide in adolescents is a major problem worldwide and previous history of suicide ideation and attempt represents the strongest predictors of future suicidal behavior. The aim of this study was to develop prediction model to identify Korean adolescents of high risk suicide (= who have history of suicide ideation/attempt in previous year) using machine learning techniques.

Authors

  • Jun Su Jung
    School of Medicine, Gachon University College of Medicine, Incheon, South Korea.
  • Sung Jin Park
    Department of Biomedical Engineering, Gachon University College of Medicine, Incheon, South Korea.
  • Eun Young Kim
    Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Kyoung-Sae Na
    Department of Psychiatry, Gachon University Gil Medical Center, Incheon, Republic of Korea. Electronic address: ksna13@gachon.ac.kr.
  • Young Jae Kim
    Department of Biomedical Engineering, College of Medicine, Gachon University, Gyeonggi-do, Republic of Korea.
  • Kwang Gi Kim
    Department of Biomedical Engineering Branch, National Cancer Center, Gyeonggi-do, South Korea.

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