A comparison of machine learning algorithms for the surveillance of autism spectrum disorder

OBJECTIVE: The Centers for Disease Control and Prevention (CDC) coordinates a labor-intensive process to measure the prevalence of autism spectrum disorder (ASD) among children in the United States. Random forests methods have shown promise in speeding up this process, but they lag behind human clas...

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Detalles Bibliográficos
Autores principales: Lee, Scott H., Maenner, Matthew J., Heilig, Charles M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6760799/
https://www.ncbi.nlm.nih.gov/pubmed/31553774
http://dx.doi.org/10.1371/journal.pone.0222907

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6760799/
https://www.ncbi.nlm.nih.gov/pubmed/31553774
http://dx.doi.org/10.1371/journal.pone.0222907

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