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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...

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Detalles Bibliográficos
Autores principales: Park, Hwanjin, Lee, Kounseok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
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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