A clustering method to study the loss of kidney function following kidney transplantation


We describe a method for studying the loss of kidney functions after renal transplantation. We monitor the changes in the estimated glomerular filtration rate (eGFR) for each patient on a monthly basis for 24 months following the transplantation. Principal components analysis is performed on the time series of eGFRs. The data is then clustered into two groups, which are then statistically analysed. We developed kernel density functions for each month on the two clusters to further validate our findings that exhibit different characteristics in their renal functions in the post-transplant periods. This can have significant monitoring and treatment implications. Copyright © 2010 Inderscience Enterprises Ltd.

Publication Title

International Journal of Biomedical Engineering and Technology