Using machine learning to determine the shared and unique risk factors for marijuana use among child-welfare versus community adolescents

OBJECTIVE: This study used machine learning (ML) to test an empirically derived set of risk factors for marijuana use. Models were built separately for child welfare (CW) and non-CW adolescents in order to compare the variables selected as important features/risk factors. METHOD: Data were from a Ti...

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Detalles Bibliográficos
Autores principales: Negriff, Sonya, Dilkina, Bistra, Matai, Laksh, Rice, Eric
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491564/
https://www.ncbi.nlm.nih.gov/pubmed/36129944
http://dx.doi.org/10.1371/journal.pone.0274998

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491564/
https://www.ncbi.nlm.nih.gov/pubmed/36129944
http://dx.doi.org/10.1371/journal.pone.0274998

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