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"These results indicate the potential for an easy and novel method for early detection of autism and development coordination disorder," said senior author Lisa Aziz-Zadeh, a professor at the USC Mrs. T.H. Chan Division of Occupational Science and Occupational Therapy. "This is especially important as motor signatures appear early in autism—usually before social symptoms. And this methodology does not involve potential biasing by the assessor."

"Early identification allows for tailored therapeutic approaches, which result in better long-term developmental outcomes," said first author Christiana Dodd Butera, a postdoctoral fellow at USC Chan. "Having the appropriate therapy for the appropriate child at the most impactful time in development would be the long-term goal of this detection work."

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Medicalxpress AI could help in the early diagnosis of autism, study finds Artificial intelligence, coupled with data from an iPad coloring game, could assist in early diagnosis of autism, a new USC study shows.
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