Diabetic Nephropathy Detection Using Bayesian Approach

Document Type : Primary Research paper

Authors

1 Assistant Professor, Department of computer Science and Engineering Bannari Amman Institute of Technology, Sathyamangalam TamilNadu, India.

2 Associate Professor, Department of computer Science and Engineering Bannari Amman Institute of Technology, Sathyamangalam TamilNadu, India.

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 initial stage
of clinical study consisted 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
status about the health of patient 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

Int. J. of Aquatic Science
Volume 12, Issue 3 - Serial Number 3
ICMMNT-2021 International Virtual Conference on Materials, Manufacturing and Nanotechnology, 30th June, 2021.
June 2021
Pages 1755-1759

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