Identifying the risk of depression in a large sample of adolescents: An artificial neural network based on random forest.

Journal: Journal of adolescence
Published Date: Jun 4, 2024

Abstract

BACKGROUND: This study aims to develop an artificial neural network (ANN) prediction model incorporating random forest (RF) screening ability for predicting the risk of depression in adolescents and identifies key risk factors to provide a new approach for primary care screening of depression among adolescents.

Authors

  • Yue Zhou
    State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, 2A Nanwei Road, Beijing 100050, China. zhouyue@imm.ac.cn.
  • Xuelian Zhang
    Department of Nosocomial Infection Control, Division of Medical Administration, The Third People's Hospital of Gansu Province, Lanzhou, Gansu, China.
  • Jian Gong
    Estuarine and Coastal Environment Research Center, Chinese Research Academy of Environmental Sciences, Beijing, 100012, P. R. China.
  • Tingwei Wang
    Department of Maternal, Child and Adolescent Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
  • Linlin Gong
    Department of Maternal, Child and Adolescent Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, China.
  • Kaida Li
    School of Computer Science and Technology, East China Normal University, Shanghai, China.
  • Yanni Wang
    Department of Maternal, Child and Adolescent Health, School of Public Health, Lanzhou University, Lanzhou, Gansu, China.

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