Testing the accuracy of an observation-based classifier for rapid detection of autism risk

Current approaches for diagnosing autism have high diagnostic validity but are time consuming and can contribute to delays in arriving at an official diagnosis. In a pilot study, we used machine learning to derive a classifier that represented a 72% reduction in length from the gold-standard Autism...

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Detalles Bibliográficos
Autores principales: Duda, M, Kosmicki, J A, Wall, D P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2014
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4150240/
https://www.ncbi.nlm.nih.gov/pubmed/25116834
http://dx.doi.org/10.1038/tp.2014.65

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4150240/
https://www.ncbi.nlm.nih.gov/pubmed/25116834
http://dx.doi.org/10.1038/tp.2014.65

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