By Aleksander Solum
HONG KONG (Reuters) – A Hong Kong scientist has developed a method to use machine learning and artificial intelligence to scan the retinas of children as young as six to detect early autism or the risk of autism and hopes to develop a commercial product this year .
Retinal scanning can help improve early detection and treatment outcomes for children, said Benny Zee, a professor at the Chinese University of Hong Kong.
“The importance of starting an early intervention is that they are still growing, they are still developing. So there is a greater chance of success,” said Zee.
His method uses a high-resolution camera with new computer software that analyzes a combination of factors, including layers of fibers and blood vessels in the eye.
The technology can be used to identify children at risk for autism and put them into treatment programs earlier, said Zee.
Seventy children were tested using the technology, 46 with autism and a control group of 24. The technology was able to identify children with autism 95.7 percent of the time. The average age tested was 13 years, with the youngest being six.
Zee’s findings were published in EClinicalMedicine, a peer-reviewed medical journal.
Autism experts welcomed their findings, but said it remains a major stigma, with parents often reluctant to believe that their children have autism, even when there are clear signs.
“Often, parents will initially be in denial,” said Dr. Caleb Knight, who runs a private therapy center for autism.
“If you had a medical test or biological marker like this, it could make it easier for parents not to deny it for longer periods and therefore the child would get treatment more quickly.”
Children with autism have to wait about 80 weeks to see a specialist in the public medical sector, according to an e-mailed statement from the Hong Kong government.
Zee told Reuters that his research is intended to be a complementary tool for professional assessment by licensed health professionals.
(Reporting by Aleksander Solum; Writing by Farah Master; Editing by Karishma Singh and Michael Perry)