Published on in Vol 9, No 6 (2021): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27793, first published .
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

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

Julie Gardner-Hoag 1, BSc, MSc;  Marlena Novack 2, BA;  Chelsea Parlett-Pelleriti 3, BA, MSc;  Elizabeth Stevens 3*, BSc, MSc, PhD;  Dennis Dixon 2*, BA, PhD;  Erik Linstead 3*, BSc, MSc, PhD

1 Schmid College of Science and Technology, Chapman University , Orange, CA, US

2 Center for Autism and Related Disorders , Woodland Hills, CA, US

3 Fowler School of Engineering, Chapman University , Orange, CA, US

*these authors contributed equally

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