Predicting Relative Risk for Diabetes Mellitus Using Association Rule Summarization in EMR

R. Sangeetha, M. Vivekanantha Moorthy

Abstract: - Diabetes is a growing epidemic of non-communicable disease which affects most of the people in the world. In order to suppress the growth of diabetes mellitus we use association rule summarization to electronic medical records to discover set of risk factors and the corresponding sub-population which represents patients at particularly high risk of developing diabetes. Usually association rule mining generates large volume of data sets which we need to summarize for any medical record or any clinical use. We incorporate four methods to find the common factors which lead to high risk of diabetes all these four methods produced summaries that described sub populations at high risk of diabetes with each method having its clear strength. According to our purpose we use bottom up summarization (BUS) algorithm which produces more suitable summary.

Keywords: data mining, association rule mining, survival analysis, association rule summarization

How to Cite?: R. Sangeetha, M. Vivekanantha Moorthy, "Predicting Relative Risk for Diabetes Mellitus Using Association Rule Summarization in EMR", Volume 4 Issue 3, March 2015, International Journal of Science and Research (IJSR), Pages: 1118-1122, https://www.ijsr.net/getabstract.php?paperid=SUB152157, DOI: https://dx.doi.org/10.21275/SUB152157