It’s difficult to diagnose infants with autism due to trouble determining whether any behavioral traits common to autism are present. This difficulty is most pronounced before the age of two, and especially before the age of one, resulting in delayed diagnoses. All that may be changing, though, thanks to artificial intelligence and its ability to predict with high accuracy which infants will be diagnosed with autism by their second year.
As detailed by a new study funded by the US National Institute of Health, predictions of future Autism Spectrum Disorder can be made based on MRI scans of an infant’s brain. The technology heavily relies on brain scans taken of infants that are at high risk of being diagnosed with autism by their second birthday.
Using 106 brain scans of high-risk infants, researchers determined that certain aspects of the brain’s maturation may be early indicators of autism. One potential indicator is a quickly growing brain, one that grows faster than normal during the age spanning 12 to 24 months. As well, the cortex may grow faster than average during this time period.
Based on this information and using brain scans taken at 6 and 12 months, a customized algorithm was able to predict which infants would end up with an autism diagnoses with an 81-percent accuracy. Knowing whether a baby is likely to be autistic may help, in certain cases, early intervention and the preparation of parents.