Intelligent and Effective Diabetes Risk Prediction System Using Data Mining

Kawsar Ahmed¹,Tasnubajesmin¹, Ushin Fatima²,Md. Moniruzzaman², Abdulla-L-Emran² and Md. Zamilur Rahman¹

¹Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Santosh, Tangail-1902

²Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail-1902

ABSTRACT:

Diabetes is not only a disease but also responsible for occurring different kinds of diseases such as heart attack, kidney disease, blindness and renal failure. With respect to Bangladesh, Diabetes is a deadly, disabling and cost disease whose risk is increasing at alarming rate. The diagnosis of diabetes is a vital and tedious task. The detection of diabetes from some important risk factors is a multi-layered problem. Initially 400 diabetes and non-diabetes patients’ data is collected from different diagnostic centre and data is pre-processed. After pre-processing data is clustered using K-means clustering algorithm for identifying relevant and non-relevant data to diabetes. Next significant frequent patterns are discovered using AprioriTid shown in Table 1 and Decision Tree algorithm shown in Table 2. Finally implement a system to predict diabetes which is easier, cost reducible and time saveable.

KEYWORDS: Data pre-processing; Data classification; AprioriTid algorithm; DT (Decision tree) algorithm; K-means clustering; Significant frequent pattern

Copy the following to cite this article: Ahmed K,Tasnubajesmin, Fatima U, Moniruzzaman Md, Abdulla-L-Emran, Rahman Md. Z. Intelligent and Effective Diabetes Risk Prediction System Using Data Mining. Orient. J. Comp. Sci. and Technol;5(2)

Copy the following to cite this URL: Ahmed K,Tasnubajesmin, Fatima U, Moniruzzaman Md, Abdulla-L-Emran, Rahman Md. Z. Intelligent and Effective Diabetes Risk Prediction System Using Data Mining. Orient. J. Comp. Sci. and Technol;5(2). Available from: http://www.computerscijournal.org/?p=2637

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