Detecting Developmental Delay and Autism Through Machine Learning Models Using Home Videos of Bangladeshi Children: Development and Validation Study.

Journal: Journal of medical Internet research
PMID: 31017583

Abstract

BACKGROUND: Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that measure between 20-100 behaviors, can span multiple appointments with trained clinicians, and take several hours to complete. In our previous work, we demonstrated the efficacy of machine learning classifiers to accelerate the process by collecting home videos of US-based children, identifying a reduced subset of behavioral features that are scored by untrained raters using a machine learning classifier to determine children's "risk scores" for autism. We achieved an accuracy of 92% (95% CI 88%-97%) on US videos using a classifier built on five features.

Authors

  • Qandeel Tariq
    Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California; Department of Biomedical Data Science, Stanford University, Stanford, California.
  • Scott Lanyon Fleming
    Department of Biomedical Data Science, Stanford University, Palo Alto, CA, United States.
  • Jessey Nicole Schwartz
    Department of Pediatrics, Division of Systems Medicine, Stanford University, California, United States of America.
  • Kaitlyn Dunlap
    Division of Systems Medicine, Department of Pediatrics, Stanford University, Palo Alto, CA, United States.
  • Conor Corbin
    Department of Biomedical Data Science, Stanford University, Palo Alto, CA, United States.
  • Peter Washington
    Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, HI 96822, USA.
  • Haik Kalantarian
    Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California; Department of Biomedical Data Science, Stanford University, Stanford, California.
  • Naila Z Khan
    Dhaka Shishu Children's Hospital, Dhaka, Bangladesh.
  • Gary L Darmstadt
    March of Dimes Prematurity Center, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA.
  • Dennis Paul Wall
    Department of Pediatrics, Division of Systems Medicine, Stanford University, California, United States of America.

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