Multi-modular AI Approach to Streamline Autism Diagnosis in Young Children

Halim Abbas, Ford Garberson, Stuart Liu-Mayo, Eric Glover & Dennis P. Wall  Scientific Reports volume 10, Article number: 5014 (2020) Cite this article 2 Altmetric | Metricsdetails Abstract Autism has become a pressing healthcare challenge. The instruments used to aid diagnosis are time and labor expensive and require trained clinicians to administer, leading to long wait times for at-risk children. We present a multi-modular, machine learning-based assessment of autism comprising three complementary modules…

Effect of Wearable Digital Intervention for Improving Socialization in Children With Autism Spectrum Disorder: A Randomized Clinical Trial

JAMA Pediatr. 2019;173(5):446-454. doi:10.1001/jamapediatrics.2019.0285 Catalin Voss, MS1; Jessey Schwartz, BA2; Jena Daniels, BS2; et al  In this randomized clinical trial of 71 children with autism spectrum disorder, children treated at home with the wearable intervention showed a significant improvement in socialization over children only receiving standard of care behavioral therapy. Read full publication here.

Machine learning for early detection of autism (and other conditions) using a parental questionnaire and home video screening.

2017 IEEE International Conference on Big Data. Existing screening tools for early detection of autism are expensive, cumbersome, time-intensive, and sometimes fall short in predictive value. In this work, we apply Machine Learning to gold standard clinical data obtained across thousands of children at risk for autism spectrum disorders to create a low-cost, quick, and easy to apply autism screening…