An Extensive Survey on Evolutionary Algorithm Based Kidney Disease Prediction

Presently, the identification of kidney disease (KD) among medical practitioners becomes popular to detect the presence of KD in an easier way and at a faster rate. Due to the huge quantity of medical database, efficient methods needed to for proper diagnosis. In general, the expert's knowledge is necessary for the classification of data to predict the presence of KDs. In the past days, statistical techniques and some machine learning algorithms are used. Recently, evolutionary algorithms (EA) become famous and several classification techniques for KD prediction have also been developed. In this paper, we made an attempt to review the existing KD prediction techniques. The review is based on different aspects such as aim, algorithm used, experimental analysis and so on. A comparison of the reviewed methods is also made interms of different criteria.