Researchers at Indiana University and Purdue University are working to improve the early diagnosis of autism in children, as the wait time for evaluations can be over a year. They conducted a study using eye tracking biomarkers at primary care clinics and found that combining clinician diagnosis with eye-tracking metrics improved the accuracy of autism diagnosis. The team plans to conduct further studies using artificial intelligence and hopes to improve access to timely and accurate diagnoses in local communities. This research aims to address the delays in autism evaluations and provide better support for primary care clinicians in diagnosing autism in young children.
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Eye-tracking technology offers earlier, more accurate autism diagnosis
