Bioinformatics Used to Predict Autism
Liu’s technology is an autism spectrum disorder (ASD) prediction model capable of reliably identifying children at high risk for ASD as early as 6 months after birth, well before the manifestation of any well-known ASD behavioral symptoms. The technology uses data from electronic medical records to reliably identify clinical indicators of ASD. This allows for earlier specialist intervention, providing children with ASD a more favorable health outcome.
Application & Market Utility
Currently, 1 out of every 68 US children has ASD, and the prevalence is rising at an alarming rate. The target customers are concerned parents, pediatricians, and social-service/early intervention agencies. Over $435 million in federal funding is provided annually for early intervention agencies. The older a child is when diagnosed with autism, the higher the medical costs required to treat the child. Therefore, insurance companies would be a strong potential customer to obtain early detection of at-risk children to initiate early intervention and reduce medical costs.
Seeking research collaboration and licensing opportunities.