Abstract
Mounting amounts of data made traditional data analysis methods impractical. Data mining (DM) tools provide a useful for alternative framework that addresses this problem. This study follows a DM technique to identify diabetic patients. We develop a model that clusters diabetes patients of a large healthcare company into different subpopulation. Consequently, we show the value of applying a DM model to identify diabetic patients.
Recommended Citation
Porter, Thomas and Green, Barbara, "Identifying Diabetic Patients: A Data Mining Approach" (2009). AMCIS 2009 Proceedings. 500.
https://aisel.aisnet.org/amcis2009/500
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