Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data--both genetic and behavioral--that are collected as part of scientific studies or a part of treatment can provide a deeper,…

Autism spectrum disorder (ASD) research has yet to leverage "big data" on the same scale as other fields; however, advancements in easy, affordable data collection and analysis may soon make this a reality. Indeed, there has been a notable increase in research literature evaluating the effectiveness of machine learning for diagnosing…

Drawing on a realist synthesis approach, this review identified qualitative data collection approaches that inform "first-person" lived experience in autism spectrum disorder (ASD) across phenotypic expression. It further drew upon methodologic approaches used in other conditions that similarly represent individuals with impaired verbal…