A Machine Learning Strategy for Autism Screening in Toddlers.

Journal: Journal of developmental and behavioral pediatrics : JDBP
Published Date: Jun 1, 2019

Abstract

OBJECTIVE: Autism spectrum disorder (ASD) screening can improve prognosis via early diagnosis and intervention, but lack of time and training can deter pediatric screening. The Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) is a widely used screener but requires follow-up questions and error-prone human scoring and interpretation. We consider an automated machine learning (ML) method for overcoming barriers to ASD screening, specifically using the feedforward neural network (fNN).

Authors

  • Luke E K Achenie
    Departments of Chemical Engineering.
  • Angela Scarpa
    Psychology.
  • Reina S Factor
    Psychology.
  • Tao Wang
    Department of Urology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Diana L Robins
    AJ Drexel Autism Institute, Drexel University, Philadelphia, PA, United States.
  • D Scott McCrickard
    Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA.

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