Cardiometabolic diseases are the top cause of preventable deaths worldwide, and the number of people who experience one or more of these conditions during their lifetime is increasing.
That's the thinking behind new research led by Assistant Professor Bing Si from Binghamton University's Thomas J. Watson College of Engineering and Applied Science. Working in collaboration with clinical scientists from Mayo Clinic and Harvard University, Si will develop novel statistical machine models to analyze thousands of young individuals' health data -; anonymized, of course -; and predict cardiometabolic risks in adolescents and young adults.
The five-year project recently received a $2.5 million R01 award from the National Institutes of Health, with $1.8 million coming directly to Binghamton. "One big challenge is that there is missingness," Si said. "If you are collecting multimodal data from thousands of people, for sure somebody will miss something. Some tests may be unreliable and we cannot use them. We are trying to use a statistical modeling approach to address that as well."
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