Data researchers use health informatics and artificial intelligence in Type 1 diabetes study

A team of data scientists from the University of Missouri has analyzed publicly available data from about 16,000 participants enrolled in the T1D Exchange Registry to learn more about people with Type 1 diabetes. The team, supported in part by a U.S. National Science Foundation grant, gathered the information through health informatics and used artificial intelligence to better understand the disease.

“We let the computer do the work of connecting millions of dots in the data to identify major contrasting patterns between individuals with and without a family history of Type 1 diabetes, and to do the statistical testing to make sure we are confident in our results,” said Chi-Ren Shyu, one of the authors of the study.

The team’s analysis resulted in some unexpected findings.

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