Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder.

Autism spectrum disorder (ASD) can be reliably diagnosed at 18 months, yet significant diagnostic delays persist in the United States. This double-blinded, multi-site, prospective, active comparator cohort study tested the accuracy of an artificial intelligence-based Software as a Medical Device designed to aid primary care healthcare providers (HCPs) in diagnosing ASD. The Device combines behavioral features from three distinct inputs (a caregiver questionnaire, analysis of two short home videos, and an HCP questionnaire) in a gradient boosted decision tree machine learning algorithm to produce either an ASD positive, ASD negative, or indeterminate output.

Prefrontal cortex, thalamus, and cerebellar volumes in adolescents and young adults with adolescent-onset alcohol use disorders and comorbid mental disorders.

Background: In adults, prefrontal, thalamic, and cerebellar brain injury is associated with excessive ethanol intake. As these brain structures are actively maturing during adolescence, we hypothesized that subjects with adolescent-onset alcohol use disorders, compared with control subjects, would have smaller brain volumes in these areas. Thus, we compared prefrontal-thalamic-cerebellar measures of adolescents and young adults with adolescent-onset alcohol use disorders (AUD, defined as DSM-IV alcohol dependence or abuse) with those of sociodemographically similar control subjects.