In recent time health industry need the data of various patients collected for the research work. Usually, doctor suggest the medicine one the basis of their past knowledge and diagnosis report of the person. This paper has to investigate the technique which has quite good to predict the CKD disease. The deep learning technique has been applying to find the accuracy of prediction disease. The data sets used for kidney disease has been taken from the UCI library. This investigation does work on various DL learning algorithm on MATLAB platform. This paper found After running MATLAB, it was discovered that the DT method has the greatest prediction value when compared to the other KNN and MLP algorithms. When DT and KNN are used instead of MLP, the execution time is much less. The accuracy, precision, and F-call value of the deep learning algorithms has been compared with exploratory bar graph where the MLP found the best for the CKD data set.

Chronic renal disease (CRD), Deep Learning Algorithm, Probabilistic Model