Behavior Imaging, a Boise, Idaho company, uses a system called the Naturalistic Observation Diagnostic Assessment. In the privacy and comfort of their own homes, families use a smart phone app to capture and upload videos of their child’s behaviors in specified situations.
Clinicians watch the videos to make remote diagnoses. More recently, the company has started training AI-like algorithms to observe and categorize behaviors. Although, the algorithms would not diagnose the children, they might be used to point clinicians to specific behaviors that might otherwise have been missed.
Another use of AI-aided diagnosis is an autism screening tool created by Cognoa in Palo Alto California. The tool uses clinically validated artificial intelligence (AI) technology to aid physicians in diagnosing ASD in children between the ages of 18 and 72 months who are at risk of developmental delay.
AI thus reduces the quantum of work by a clinician and therefore speeds up the ASD diagnoses pipeline. We can conclude that AI is of great value in ASD research and the challenging problems related to ASD are ripe for the application of AI/ML technologies. EinNext R&D aims to develop promising screening tools to help decrease the length of time and cost required for diagnosis of ASD.