Tool leverages computer vision and machine learning to screenings in low-resource environments
- Date:
- February 26, 2019
- Source:
- University of Southern California
- Summary:
- Scientists have developed a new tool that can screen children for fetal alcohol spectrum disorder (FASD) quickly and affordably, making it accessible to more children in remote locations worldwide.
Scientists at the University of Southern California (USC), Queen’s University (Ontario) and Duke University have developed a new tool that can screen children for fetal alcohol spectrum disorder (FASD) quickly and affordably, making it accessible to more children in remote locations worldwide.
The tool uses a camera and computer vision to record patterns in children’s eye movements as they watch multiple one-minute videos, or look towards/away from a target, and then identifies patterns that contrast to recorded eye movements by other children who watched the same videos or targets. The eye movements outside the norm were flagged by the researchers as children who might be at-risk for having FASD and need more formal diagnoses by healthcare practitioners.
The technique was described in a study “Detection of Children/Youth With Fetal Alcohol Spectrum Disorder Through Eye Movement, Psychometric, and Neuroimaging Data,” by Chen Zhang, Angelina Paolozza, Po-He Tseng, James N. Reynolds, Douglas P. Munoz and Laurent Itti, which appeared in Frontiers in Neurology.
According to the paper’s corresponding author, Laurent Itti, a professor of computer science, psychology and neuroscience at USC, FASD is still quite difficult to diagnose — a professional diagnosis can take a long time with the current work up taking as much as an entire day.
“There is not a simple blood test to diagnose FASD. It is one of those spectrum disorders where there is a broad range of the disorder. It is medically very challenging and it is co-morbid with other conditions. The current gold standard is subjective, as it involves a battery of tests and clinical evaluation. It is also costly.”
Click here for full article.
Story Source:
Materials provided by University of Southern California. Note: Content may be edited for style and length.
Journal Reference:
- Chen Zhang, Angelina Paolozza, Po-He Tseng, James N. Reynolds, Douglas P. Munoz, Laurent Itti. Detection of Children/Youth With Fetal Alcohol Spectrum Disorder Through Eye Movement, Psychometric, and Neuroimaging Data. Frontiers in Neurology, 2019; 10 DOI: 10.3389/fneur.2019.00080