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Auteur Jennifer GILLIS |
Documents disponibles écrits par cet auteur (1)
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Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis / Ira L. COHEN in Journal of Autism and Developmental Disorders, 46-9 (September 2016)
[article]
Titre : Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis Type de document : Texte imprimé et/ou numérique Auteurs : Ira L. COHEN, Auteur ; Xudong LIU, Auteur ; Melissa HUDSON, Auteur ; Jennifer GILLIS, Auteur ; Rachel N. S. CAVALARI, Auteur ; Raymond G. ROMANCZYK, Auteur ; Bernard Z. KARMEL, Auteur ; Judith M. GARDNER, Auteur Article en page(s) : p.3006-3022 Langues : Anglais (eng) Mots-clés : Level 2 screeners Autism Spectrum Disorder Decision trees Data mining Machine learning Seizures Monoamine Oxidase A Genotype Phenotype Subgroups Index. décimale : PER Périodiques Résumé : In order to improve discrimination accuracy between Autism Spectrum Disorder (ASD) and similar neurodevelopmental disorders, a data mining procedure, Classification and Regression Trees (CART), was used on a large multi-site sample of PDD Behavior Inventory (PDDBI) forms on children with and without ASD. Discrimination accuracy exceeded 80 %, generalized to an independent validation set, and generalized across age groups and sites, and agreed well with ADOS classifications. Parent PDDBIs yielded better results than teacher PDDBIs but, when CART predictions agreed across informants, sensitivity increased. Results also revealed three subtypes of ASD: minimally verbal, verbal, and atypical; and two, relatively common subtypes of non-ASD children: social pragmatic problems and good social skills. These subgroups corresponded to differences in behavior profiles and associated bio-medical findings. En ligne : http://dx.doi.org/10.1007/s10803-016-2843-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=292
in Journal of Autism and Developmental Disorders > 46-9 (September 2016) . - p.3006-3022[article] Using the PDD Behavior Inventory as a Level 2 Screener: A Classification and Regression Trees Analysis [Texte imprimé et/ou numérique] / Ira L. COHEN, Auteur ; Xudong LIU, Auteur ; Melissa HUDSON, Auteur ; Jennifer GILLIS, Auteur ; Rachel N. S. CAVALARI, Auteur ; Raymond G. ROMANCZYK, Auteur ; Bernard Z. KARMEL, Auteur ; Judith M. GARDNER, Auteur . - p.3006-3022.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 46-9 (September 2016) . - p.3006-3022
Mots-clés : Level 2 screeners Autism Spectrum Disorder Decision trees Data mining Machine learning Seizures Monoamine Oxidase A Genotype Phenotype Subgroups Index. décimale : PER Périodiques Résumé : In order to improve discrimination accuracy between Autism Spectrum Disorder (ASD) and similar neurodevelopmental disorders, a data mining procedure, Classification and Regression Trees (CART), was used on a large multi-site sample of PDD Behavior Inventory (PDDBI) forms on children with and without ASD. Discrimination accuracy exceeded 80 %, generalized to an independent validation set, and generalized across age groups and sites, and agreed well with ADOS classifications. Parent PDDBIs yielded better results than teacher PDDBIs but, when CART predictions agreed across informants, sensitivity increased. Results also revealed three subtypes of ASD: minimally verbal, verbal, and atypical; and two, relatively common subtypes of non-ASD children: social pragmatic problems and good social skills. These subgroups corresponded to differences in behavior profiles and associated bio-medical findings. En ligne : http://dx.doi.org/10.1007/s10803-016-2843-0 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=292