Improving Performance of Diagnosis System for Diabetes Using Data Mining Techniques


Improving Performance of Diagnosis System for Diabetes Using Data Mining Techniques

D.Sheila Freeda, Dr. Lilly Florence

D.Sheila Freeda, Dr. Lilly Florence "Improving Performance of Diagnosis System for Diabetes Using Data Mining Techniques" Published in International Journal of Trend in Research and Development (IJTRD), ISSN: 2394-9333, Special Issue | PCIT-15 , December 2015, URL: http://www.ijtrd.com/papers/IJTRD1321.pdf

Traditionally Diabetics has been diagnosed using overall cholesterol testing and a detailed lab test for individualcholesterols (HDL/LDL/ VLDL) etc and usually doctors asses the risk and recommend cholesterol test based on age, hereditary, High blood pressure , heart disease, stroke etc and it is usually predicted using these factors as well as environment and life style. However, there could be more factors and relationships both in the way to discover diabetics as well as analysis of effective cure. For that datamining techniques and tools can be used to bring out all the relationships and changing patterns. Datamining is a effective way to analyses and predict structured and unstructured data using techniques such as clustering, association, classification prediction and visualization. In tis paper we are analyzing the previous researches and relationships and the various opportunity that exists in improving the diagnosis as well as effective treatment using data mining tools and techniques.

Data Mining, Cholesterol, Heart Disease, Diabetes.


Special Issue | PCIT-15 , December 2015

2394-9333

IJTRD1321
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