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Discovery of Significant Parameters in Kidney Dialysis Data Sets by K-Means Algorithm

Ravindra, B V and Sriraam, N (2014) Discovery of Significant Parameters in Kidney Dialysis Data Sets by K-Means Algorithm. In: Proceedings of International Conference on Circuits, Communication, Control and Computing, 21-22 NOVEMBER 2014, MSRIT, Bangalore, India.

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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

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Hemodialysis, Survival, kidney failure; k-means clustering
Subjects: Information Sciences > MCIS Manipal
Depositing User: MIT Library
Date Deposited: 11 Apr 2016 16:11
Last Modified: 11 Apr 2016 16:11

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