Can you tell us a little bit more about your research and what you've been doing recently in your lab?

So as you know, CVI stands for cerebral or cortical visual impairment, and it's one of the leading causes of pediatric visual impairment in the US.

This is where the ocular anatomy may be normal, but there is decreased vision or visual dysfunction due to visual pathways in the brain being affected by things like hydrocephalus, trauma, hypoxic ischemic encephalopathy, or prematurity.

And there is no evidence-based medical treatment for CVI, which makes it very difficult for us to know how to best manage these patients in our clinic.

Part of the reason we don't have evidence-based treatment is that we can't even really run clinical trials because we don't have a good outcome measure to measure the severity of CVI because standard pediatric ophthalmology exam techniques don't really capture the higher level visual perceptual problems that kids with CVI have.

So our lab has been using eye tracking to detect various things, including visual attention to higher and lower level visual characteristics using eye tracking.

So eye tracking involves a child looking at a computer monitor while a special camera tracks the direction of eye gaze with high accuracy.

So I think AI will ultimately, hopefully, give us just another tool, and hopefully it'll help more patients, including those with developmental disorders, even if the initial study did not focus on them, it still may be useful and will be another tool that will help address access to care.