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Abstract: The ability to determine an infant's likelihood of developing
autism via a relatively simple neurological measure would constitute an important
scientific breakthrough. In their recent publication in this journal, Bosl and
colleagues claim that a measure of EEG complexity can be used to detect, with very
high accuracy, infants ... read moreat high risk for autism (HRA). On the surface, this appears to
be that very scientific breakthrough and as such the paper has received widespread
media attention. But a close look at how these high accuracy rates were derived tells
a very different story. This stems from a conflation between "high risk" as a
population-level property and "high risk" as a property of an individual. We describe
the approach of Bosl et al. and examine their results with respect to baseline
prevalence rates, the inclusion of which is necessary to distinguish infants with a
biological risk of autism from typically developing infants with a sibling with
autism. This is an important distinction that should not be
overlooked.
Keywords: Autism Spectrum Disorder, control/comparison group, high risk
for autism.
Springer Open.read less
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