Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study

Unsupervised Machine Learning for Identifying Challenging Behavior Profiles to Explore Cluster-Based Treatment Efficacy in Children With Autism Spectrum Disorder: Retrospective Data Analysis Study

BackgroundChallenging behaviors are prevalent among individuals with autism spectrum disorder; however, research exploring the impact of challenging behaviors on treatment response is lacking. ObjectiveThe purpose of this study was to identify types of autism spectrum disorder based on e...

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Bibliographic Details
Main Authors: Gardner-Hoag, Julie, Novack, Marlena, Parlett-Pelleriti, Chelsea, Stevens, Elizabeth, Dixon, Dennis, Linstead, Erik
Format: Article
Language:English
Published: JMIR Publications 2021-06-01
Series:JMIR Medical Informatics
Online Access:https://medinform.jmir.org/2021/6/e27793

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https://medinform.jmir.org/2021/6/e27793

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