AI Device May Speed Autism Diagnoses in Rural Areas

An artificial intelligence-powered medical device could significantly reduce wait times for autism spectrum disorder evaluations in rural and underserved U.S. communities, according to new research from the University of Missouri.

The device, known as CanvasDx and developed by Cognoa Inc., integrates AI algorithms with patient data to predict autism diagnoses. It outputs a positive, negative or indeterminate result based on inputted information. In areas like Missouri, where families often face nearly year-long delays for specialist appointments, the tool offers primary care clinicians a way to conduct evaluations locally.

Lead researcher Kristin Sohl, a pediatrician at MU Health Care and professor of child health at the University of Missouri School of Medicine, collaborated with Cognoa to evaluate the FDA-approved device. The study focused on primary care settings lacking specialized autism services, using the ECHO Autism program, which trains clinicians in autism care across Missouri and beyond.

Study Details and Results

The research examined data from 80 children in rural Missouri. CanvasDx produced determinate results -- either positive or negative for autism -- in 52% of cases. Notably, the device recorded no false positives or false negatives and aligned fully with clinicians' independent diagnoses.

For the remaining 48% of cases, the tool returned indeterminate results, underscoring the importance of clinician expertise. Sohl emphasized that while AI provides objective support, it must complement trained professionals. "Devices like CanvasDx, especially when used by autism-experienced clinicians, can help accelerate diagnosis," she said.

Participants were primarily from rural areas, where access to specialty centers requires extensive travel. The average distance to such facilities was 97 miles, often involving significant time and fuel costs for families. By enabling local evaluations, the device facilitated diagnoses 5-7 months earlier than traditional waitlists, allowing quicker access to supportive services.

The study, published in JMIR Formative Research (DOI: 10.2196/80733), highlights CanvasDx's potential to streamline processes without compromising accuracy. It processed caregiver reports, developmental screenings and video observations to generate predictions, aiding clinicians in decision-making.

Broader Implications for Autism Care

Autism evaluations remain a bottleneck in U.S. healthcare, particularly in rural regions. The Centers for Disease Control and Prevention estimates that about 1 in 36 children has autism, yet diagnostic disparities persist due to limited specialists. In Missouri, wait times average 10-12 months, delaying interventions that can improve long-term outcomes.

Sohl, founder and executive director of the ECHO Autism program and medical director of the Missouri Telehealth Network, views the device as a step toward equitable care. "Our mission is to increase access to best practices for autism care across rural and underserved communities," she said. Early identification enables individualized support, such as behavioral therapies and educational accommodations, which are critical for child development.

The research also calls for enhanced clinician education. While CanvasDx adds data-driven insights, its indeterminate outputs in nearly half of cases reinforce the need for comprehensive training in autism assessment. Sohl noted that integrating such tools could reduce burdens on families and healthcare systems alike.

Challenges and Future Directions

Despite promising results, limitations exist. The study's sample size of 80 children is modest, and broader testing is needed across diverse populations. Indeterminate results may still require referrals to specialists, though at a faster pace than current systems.

Ongoing efforts through programs like ECHO Autism aim to equip more primary care providers with the skills to use AI aids effectively. Sohl advocates for policies supporting telehealth and device adoption to bridge urban-rural gaps.

As autism prevalence rises, innovations like CanvasDx represent a scalable solution. By embedding AI in routine care, the approach could transform how diagnoses are made, ensuring timely support for affected children and families nationwide.