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Using Boosted Machine Learning to Predict Suicidal Ideation by Socioeconomic Status among Adolescents
(1) Background: This study aimed to use machine learning techniques to identify risk factors for suicidal ideation among adolescents and understand the association between these risk factors and socioeconomic status (SES); (2) Methods: Data from 54,948 participants were analyzed. Risk factors were i...
Autores principales: | Park, Hwanjin, Lee, Kounseok |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9505188/ https://www.ncbi.nlm.nih.gov/pubmed/36143142 http://dx.doi.org/10.3390/jpm12091357 |
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