Author
New, Alexander; Rashid, Sabbir; Erickson, John S.; McGuinness, Deborah L.; Bennett, Kristin P.
Other Contributors
Date Issued
2018-11-27
Degree
Terms of Use
Abstract
One primary task of population health analysis is the identification of risk factors that, for some subpopulation, have a significant association with some health condition. Examples include finding lifestyle factors associated with chronic diseases and finding genetic mutations associated with diseases in precision health. We develop a combined semantic and machine learning system that uses a health risk ontology and knowledge graph (KG) to dynamically discover risk factors and their associated subpopulations. Semantics and the novel supervised cadre model make our system explainable. Future population health studies are easily performed and documented with provenance by specifying additional input and output KG cartridges.;
Department
Publisher
arXiv
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