Prediction of Autism at 3 Years from Behavioural and Developmental Measures in High-Risk Infants: A Longitudinal Cross-Domain Classifier Analysis

Autor: Bussu, G., Jones, E. J. H., Charman, T., Johnson, M. H., Buitelaar, J. K., Baron-Cohen, S., Bedford, R., Bolton, P., Blasi, A., Chandler, S., Cheung, C., Davies, K., Elsabbagh, M., Fernandes, J., Gammer, I., Garwood, H., Gliga, T., Guiraud, J., Hudry, K., Liew, M., Lloyd-Fox, S., Maris, H., O’Hara, L., Pasco, G., Pickles, A., Ribeiro, H., Salomone, E., Tucker, L., Volein, A.
Přispěvatelé: Bussu, G, Jones, E, Charman, T, Johnson, M, Buitelaar, J, Baron-Cohen, S, Bedford, R, Bolton, P, Blasi, A, Chandler, S, Cheung, C, Davies, K, Elsabbagh, M, Fernandes, J, Gammer, I, Garwood, H, Gliga, T, Guiraud, J, Hudry, K, Liew, M, Lloyd-Fox, S, Maris, H, O'Hara, L, Pasco, G, Pickles, A, Ribeiro, H, Salomone, E, Tucker, L, Volein, A
Rok vydání: 2018
Předmět:
Male
Longitudinal study
Autism Spectrum Disorder
Autism
High-risk
Early prediction
behavioral disciplines and activities
psyc
03 medical and health sciences
Child Development
All institutes and research themes of the Radboud University Medical Center
0302 clinical medicine
Risk Factors
mental disorders
Machine learning
Developmental and Educational Psychology
medicine
Humans
0501 psychology and cognitive sciences
Motor skill
Original Paper
Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7]
Individual prediction
Siblings
05 social sciences
Area under the curve
Infant
220 Statistical Imaging Neuroscience
Cognition
medicine.disease
Child development
Vineland Adaptive Behavior Scale
Autism spectrum disorder
Child
Preschool
Infant Behavior
Data integration
Female
Psychology
030217 neurology & neurosurgery
050104 developmental & child psychology
Clinical psychology
Zdroj: Journal of Autism and Developmental Disorders, 48, 2418-2433
Bussu, G, Jones, E J H, Charman, T, Johnson, M H, Buitelaar, J K, Baron-Cohen, S, Bedford, R, Bolton, P, Blasi, A, Chandler, S, Cheung, C, Davies, K, Elsabbagh, M, Fernandes, J, Gammer, I, Garwood, H, Gliga, T, Guiraud, J, Hudry, K, Johnson, M H, Liew, M, Lloyd-Fox, S, Maris, H, O’Hara, L, Pasco, G, Pickles, A, Ribeiro, H, Salomone, E & Tucker, L & Volein, A 2018, ' Prediction of Autism at 3 Years from Behavioural and Developmental Measures in High-Risk Infants : A Longitudinal Cross-Domain Classifier Analysis ', Journal of Autism and Developmental Disorders, pp. 1-16 . https://doi.org/10.1007/s10803-018-3509-x
Journal of Autism and Developmental Disorders
Journal of Autism and Developmental Disorders, 48, 7, pp. 2418-2433
ISSN: 0162-3257
DOI: 10.1007/s10803-018-3509-x
Popis: We integrated multiple behavioural and developmental measures from multiple time-points using machine learning to improve early prediction of individual Autism Spectrum Disorder (ASD) outcome. We examined Mullen Scales of Early Learning, Vineland Adaptive Behavior Scales, and early ASD symptoms between 8 and 36 months in high-risk siblings (HR; n = 161) and low-risk controls (LR; n = 71). Longitudinally, LR and HR-Typical showed higher developmental level and functioning, and fewer ASD symptoms than HR-Atypical and HR-ASD. At 8 months, machine learning classified HR-ASD at chance level, and broader atypical development with 69.2% Area Under the Curve (AUC). At 14 months, ASD and broader atypical development were classified with approximately 71% AUC. Thus, prediction of ASD was only possible with moderate accuracy at 14 months. Electronic supplementary material The online version of this article (10.1007/s10803-018-3509-x) contains supplementary material, which is available to authorized users.
Databáze: OpenAIRE
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