Prediction of autism spectrum disorder diagnosis using nonlinear measures of language-related EEG at 6 and 12 months

Abstract Background Early identification of autism spectrum disorder (ASD) provides an opportunity for early intervention and improved developmental outcomes. The use of electroencephalography (EEG) in infancy has shown promise in predicting later ASD diagnoses and in identifying neural mechanisms u...

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Autores principales:	Fleming C. Peck, Laurel J. Gabard-Durnam, Carol L. Wilkinson, William Bosl, Helen Tager-Flusberg, Charles A. Nelson
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	EEG Autism Language development Machine learning Infant Sensitive period Neurosciences. Biological psychiatry. Neuropsychiatry RC321-571
Acceso en línea:	https://doaj.org/article/c9ef04b660b94503944c06ab407cdf9b
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Prediction of autism spectrum disorder diagnosis using nonlinear measures of language-related EEG at 6 and 12 months

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