Case Study: University of North Carolina improves early childhood caries screening with Google Cloud AutoML

University of North Carolina screens 8,000+ children for ECC with Google for Education

The University of North Carolina's Adams School of Dentistry sought to analyze a vast dataset of over 8,000 children to better understand and screen for Early Childhood Caries (ECC). Their challenge was to process thousands of variables to identify which factors best predicted the disease in order to develop an effective screening tool.

By using Google for Education's Google Cloud AutoML Tables, the team was able to quickly build and analyze custom machine learning models. This solution from Google for Education successfully identified that a simple model using a child's age and a parent's oral health assessment was the most accurate predictor. The research won national awards and is being developed into a public, web-based screening tool to enhance the use of public health data for the greater good.

University of North Carolina