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Risk level analysis for diabetic nephropathy using data mining techniques

varuna sivasakthi

Abstract


Diabetic nephropathy is a disease which affects the kidney leading to end stage renal disease. This problem occurs in patients affected by type2 diabetes. The earliest clinical manifestation is of microalbminuria which is a protein that is released in excess amount in patients affected by diabetic nephropathy. This research work aims at analyzing the risk factors involved in causing diabetic nephropathy using Bayesian classifier. The risk factors such as hypertension, hyperlipidemia, obesity, sedentary life style, urbanization and changing diets are analyzed and their probability in causing diabetic nephropathy is analyzed. Bayesian classifier is used to provide a decision support system to monitor the health status of the patient and and reduce the risk of creating nephropathy. The implementation is carried out using MATLAB and the risk is classified as low and high based on the probability.

Keywords: Bayesian classifier; Nephropathy; Type2 diabetes; Probability; Decision Support System

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References


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DOI: https://doi.org/10.37628/ijods.v3i2.297

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