A Novel Approach for Chronic Kidney Disease Identification Empowered with Fuzzy Logic

Abstract

Chronic kidney disease (CKD) is a non-communicable condition that often leads to renal failure, which is when the kidneys are no longer able to filter waste and excess fluid from the body's circulation. Early detection of CKD can slow the progression of the illness and reduce the overall cost of treatment. In this work, a novel approach for identifying CKD using a fuzzy logic system is proposed. The fuzzy system includes eight input parameters such as weight, age, serum creatinine, diastolic blood pressure, systolic blood pressure, glomerular filtration rate, blood glucose, and smoking. The output variable describes a specific patient’s stage of chronic renal disease based on these input factors. The output will indicate the current stage of a patient’s kidney disease. This system can therefore assist specialists in determining the stage of chronic renal disease. The MATLAB software is used to create the fuzzy system. The proposed system is tested on a real data set of patients and the results obtained are promising.