Data Mining Techniques: Contemporary Amalgam System to Predict Diabetes.
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2016, Vol 18, Issue 4
Abstract
Abstract: Diabetes is a never ending disease which affects many major organs of the human body, including heart, blood vessels, nerves, eyes and kidneys. The World Health Organization (WHO) estimates that nearly 200 million people all over the world suffer from diabetes and this number is likely to be doubled by 2030. In India,there are nearly 50 million diabetics, according to the statistics of the International Diabetes Federation. To identify the diabetes mellitus the medical practitioner will diagnose the pattern consists of observable symptoms and based on the all respective test. The risk and costs may be differing according to the patient condition. Inthis paper, we are providing a novel approach is to act like a medical practitioner who will identify the type of diabetes and this will provide some suggestions to regulate blood sugar level and also notify the risk factor of the patient like heart attack, nerves problem will it affect the eye or the kidney. There are two different and modern approaches are used to develop this automated model. C5.0 algorithm is going to be used to classify the patient data and fuzzy inference for analyzing data. We also achieve accurate results through analyzing various data.
Authors and Affiliations
Vimalavinnarasi. A
Keywords
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