- December 10, 2021
WHAT IT IS ABOUT
In a study, whose findings were published in the journal Complex & Intelligent Systems, the researchers examined and tested two sets of nonlinear, highly distinctive features of EEG signals extracted from children aged four (4) to 13. One set belonged to 40 children diagnosed with Autism Spectrum Disorder (ASD), while the other set was extracted from 37 children without any neurodevelopmental disorders. They were able to identify three distinct combinations of the EEG signal features that were “strongly predictive” of autism.
WHY IT MATTERS
In Australia, more than 150,000 children are estimated to have autism. At present, no medical test or blood test is available to make a definitive diagnosis of the disorder. It can take years before a doctor can diagnose children with ASD by examining a child’s behaviour and development over a period of time. According to a media release, the researchers are now embarking on the next stage of their study where they will gather more data to test and develop a cloud-based system to automatically detect autism in a single brain scan.
The proposed cloud-based system will feed live data from a brain scan into a cloud service that runs on machine learning algorithms to analyze and rapidly classify the EEG signals into ASD and non-ASD categories. This sort of system, Gururajan said, could be potentially used to spot other neurological diseases affecting children, such as attention-deficit hyperactivity disorder and epilepsy.
THE LARGER TREND
In the US, there is an existing diagnostic support tool that helps pediatricians and primary care clinicians evaluate and diagnose autism in children. The Canvas Dx by pediatric behavioral health firm Cognoa uses AI algorithms to analyze videos showing a child’s behavior and responses to questions. The software serves as an aid in the diagnosis of ASD patients ages five (5) to 18; it is not intended for use as a standalone diagnostic tool. Cognoa has recently received an FDA De Novo classification for its device.
ON THE RECORD
“This system could improve patient outcomes by a great deal because the earlier we’re able to detect and diagnose children with autism, the sooner families can start to make decisions about therapies, treatments and supports,” Prof. Gururajan stated. “There is a real need for an automated diagnostic tool to aid healthcare professionals in diagnosing ASD accurately and early, particularly clinicians who may not have a lot of experience with children with autism,” he added.
REFERENCE: HIMSS; 26 AUG 2021; Adam Ang