Long waits for autism evaluations are common, especially in rural areas where families must travel to specialty centres. Researchers at the University of Missouri School of Medicine, led by Kristin Sohl, partnered with Cognoa to test CanvasDx, an FDA-approved medical device. CanvasDx uses AI algorithms together with patient data to predict a positive or negative autism diagnosis; when the information is unclear it reports an "indeterminate" result.
The project used the ECHO Autism community, which trains primary care clinicians across Missouri and beyond. The aim was to see whether CanvasDx could support primary care clinicians in places without nearby autism specialty services and increase local access to evaluation.
In the study the average travel distance to specialty care was 97 miles, and keeping care local meant families received a diagnosis 5–7 months earlier. In a group of 80 children the device produced determinate results for 52% and did not give any false positives or false negatives; it never contradicted a clinician's diagnosis.
Difficult words
- evaluation — process to judge or measure a medical conditionevaluations
- specialty — specific area of medical care or practice
- partner — work together with another person or grouppartnered
- algorithm — a set of rules a computer followsalgorithms
- indeterminate — not clearly positive or negative result
- clinician — healthcare professional who treats patientsclinicians, clinician's
- false positive — test result says condition exists but doesn'tfalse positives
Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.
Discussion questions
- Do you think primary care clinicians should use AI tools like CanvasDx? Why or why not?
- How would receiving a diagnosis 5–7 months earlier change care for a family in a rural area?
- What other challenges might families still face even if local autism evaluations are available?
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