A STUDY ON DIABETES HEALTHCARE PATHWAY PROCESS USING DATA MINING TECHNIQUES

ABSTRACT Data mining techniques are widely used in medical diagnosis for patterns recognition, processing and treatment. Diabetes is considered as a metabolic disease where high blood sugar levels sustain over a period of time. In this paper we concentrate on the Diabetes Personalized Healthcare Pathways by accessing diabetes patient's data that are sampled (300Nos.). These data are collected and then Pre-Processed for research purpose. Later K-means algorithms and KDD algorithms are implemented for Prediction, Classifying and Clustering that are related to several data mining techniques in order to predict diabetes. The proposed thesis of data-mining techniques in the field of Diabetes Personalized health care will lead to useful extraction of valuable knowledge and to generate new hypothesis for further research/experimentation in this field. The derived results can be used for both scientific research and real-life practices to enhance the quality of diabetes patients. Through this research data mining can be used in many fields of medicine and can be developed to give doctors help to provide effective treatment and early diagnosis of several diseases through the result obtained using data mining techniques. Keywords:-Data mining, Data pre-processing, Classifier, Prediction, Clustering.