Discovery of significant parameters in kidney dialysis data sets by K-means algorithm

The contributing factors for kidney dialysis such as creatinine, sodium, urea plays an important role in deciding the survival prediction of the patients as well as the need for undergoing kidney transplantation. Several attempts have been made to derive automated decision making procedure for earlier prediction. This preliminary study investigates the importance of clustering technique for identifying the influence of kidney dialysis parameters. A simple K-means algorithm is used to elicit knowledge about the interaction between many of these measured parameters and patient survival. The clustering procedure predicts the survival period of the patients who is undergoing the dialysis procedure.