Classification of HRS using SVM

Abstract

The kidney diseases are one of the main causes of death around the world. Automatic detection and classification of kidney related diseases are important for diagnosis of kidney irregularities. Hepatorenal Syndrome (HRS) is a lifethreatening medical condition when kidney fails due to liver failure. The treatment to such cases is liver transplant, or dialysis for temporary basis. This paper proposed to apply the Support Vector Machine (SVM) classification for diagnosis of HRS. The results were evaluated using realistic data from hospitals. RBF kernel function is used along with SVM. The results show a significant accuracy of 95%.