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Direct linkBussu, 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. – Journal of Autism and Developmental Disorders, 2018
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…
Descriptors: Prediction, Autism, Symptoms (Individual Disorders), Classification
