Predicting low cognitive ability at age 5 using machine learning methods and birth cohort data

BACKGROUND: Early intervention is essential to address disparities in cognitive development. Current developmental screening will not detect the vast majority of children who go on to have below average cognitive ability at school age. In this study, we applied the random forest (RF) algorithm, a hi...

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Detalles Bibliográficos
Autores principales: Bowe, A, Staines, A, McCarthy, F, Lightbody, G, Murray, D
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Poster Displays
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9593595/
http://dx.doi.org/10.1093/eurpub/ckac131.422

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9593595/
http://dx.doi.org/10.1093/eurpub/ckac131.422

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