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Image Credit: Placidplace |
With a single flash of light to the eye, artificial intelligence (AI) could deliver a faster and more accurate way to diagnose autism spectrum disorder (ASD) in children, according to new research from the University of South Australia and Flinders University.
Using an electroretinogram (ERG) - a diagnostic test that measures the electrical activity of the retina in response to a light stimulus – researchers have deployed AI to identify specific features to classify ASD.
Measuring retinal responses of 217 children aged 5-16 years (71 with diagnosed ASD and 146 children without an ASD diagnosis), researchers found that the retina generated a different retinal response in the children with ASD as compared to those who were neuro typical.
The team also found that the strongest biomarker was achieved from a single bright flash of light to the right eye, with AI processing significantly reducing the test time. The study found that higher frequency components of the retinal signal were reduced in ASD.
Conducted with University of Connecticut and University College London, the test could be further evaluated to see if these results could be used to screen for ASD among children aged 5 to 16 years with a high level of accuracy.