A predictive model for kidney failure E-health

Big data is the large set of dataset. It involves extraction, selection, analyzing and interpolation of data. Big data is used wide assortment in medical fields for analyzing the patient's medical history, prediction of future effects and clinical decision making. It can also be used as a tool to store large number of data. It helps us to understand the diseases and also paves way to predict the disease and its future effects caused by the disease. In this paper we use RBFNN (Radial Basis Function Neural Network) with classifier algorithm with the use of parameters to determine the condition of a patient as a normal or a kidney failure patient. The proposed method reveals the stages of the kidney failure patient and treatment and clinical decision.