Korean Journal of Artificial Intelligence (한국인공지능학회지)

Korea Artificial Intelligence Association (한국인공지능학회)
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Analysis of Adolescent Suicide Factors based on Random Forest Machine Learning Algorithm

  • Received : 2023.01.20
  • Accepted : 2023.09.05
  • Published : 2023.09.30
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Abstract

The purpose of this study is to identify and analyze suicide factors of adolescents using the Random Forest algorithm. According to statistics on the cause of death by the National Statistical Office in 2019, suicide was the highest cause of death in the 10-19 age group, which is a major social problem. Using machine learning algorithms, research can predict whether individual adolescents think of suicide without investigating suicidal ideation and can contribute to protecting adolescents and analyzing factors that affect suicide, establishing effective intervention measures. As a result of predicting with the random forest algorithm, it can be said that the possibility of identifying and predicting suicide factors of adolescents was confirmed. To increase the accuracy of the results, continuous research on the factors that induce youth suicide is necessary.

Keywords

Acknowledgement

This work was supported by the research grant of the KODISA Scholarship Foundation in 2023.

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