Publications

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…

ASD symptoms in toddlers and preschoolers: An examination of sex differences

Rosmary Ros‐Demarize, Catherine Bradley, Stephen M. Kanne, Zachary Warren, Andrea Boan, Clara Lajonchere, Justine Park, Laura Arnstein Carpenter Abstract Although considerable work has documented higher prevalence rates of autism spectrum disorder (ASD) in boys, fewer studies have focused on sex differences within samples of young children at‐risk for ASD. This study examined sex differences in ASD symptom domains and ASD screening outcomes…

In-Home Speech and Language Screening for Young Children: A Proof-of-Concept Study Using Interactive Mobile Storytime

Du Y1,2, Abbas H2, Taraman S1,2,3, Segar S2, Bischoff N2. Author information 1University of California, Irvine, CA, USA.2Cognoa Inc., Palo Alto, CA, USA.3Children’s Hospital of Orange County, Orange, CA, USA. Abstract Early identification and intervention of speech and language delays in children contribute to better communication and literacy skills for school readiness and are protective against behavioral and mental health problems. Through collaboration between…

When Are We Sure? Predictors of Clinician Certainty in the Diagnosis of Autism Spectrum Disorder.

Journal of Autism and Developmental Disorders. Abstract Differential diagnosis of autism spectrum disorder (ASD) is challenging, and uncertainty regarding a child’s diagnosis may result in under-identification or prolonged diagnostic pathways. The current study examined diagnostic certainty, or how sure clinicians were that their diagnosis was accurate, among 478 toddler and preschool-aged children referred for possible ASD to academic medical specialty…

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 Abstract Importance  Autism behavioral therapy is effective but expensive and difficult to access. While mobile technology–based therapy can alleviate wait-lists and scale for increasing demand, few clinical trials exist to support its use for autism spectrum disorder (ASD) care. Objective  To evaluate the efficacy of Superpower Glass, an artificial intelligence–driven wearable behavioral intervention for improving social outcomes…

Mobile detection of autism through machine learning on home video: A development and prospective validation study.

Plos Medicine. Published: November 27, 2018. Abstract Background The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access to therapy. We hypothesize that the use of machine learning analysis on home video…

Exploratory study examining the at-home feasibility of a wearable tool for social-affective learning in children with autism.

npj Digital Medicine. Published: 02 August 2018. Abstract Although standard behavioral interventions for autism spectrum disorder (ASD) are effective therapies for social deficits, they face criticism for being time-intensive and overdependent on specialists. Earlier starting age of therapy is a strong predictor of later success, but waitlists for therapies can be 18 months long. To address these complications, we developed Superpower…

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