Prediction of suicidal ideation among preadolescent children with machine learning models: A longitudinal study.

Journal: Journal of affective disorders
PMID: 38387673

Abstract

BACKGROUND: Machine learning (ML) has been widely used to predict suicidal ideation (SI) in adolescents and adults. Nevertheless, studies of accurate and efficient models of SI prediction with preadolescent children are still needed because SI is surprisingly prevalent during the transition into adolescence. This study aimed to explore the potential of ML models to predict SI among preadolescent children.

Authors

  • Chi Yang
    Molecular Medicine Research Center, Chang Gung University, 33302 Taoyuan, Taiwan.
  • E Scott Huebner
    Department of Psychology, University of South Carolina, Columbia, SC 29208, USA.
  • Lili Tian
    Philosophy and Social Science Laboratory of Reading and Development in Children and Adolescents, South China Normal University, Ministry of Education, Guangzhou 510631, People's Republic of China. Electronic address: tianlili@m.scnu.edu.cn.

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