Confined Routing in Wireless Sensor Networks: A Study on Intended at Motion

Abstract

One of the grave problems after kidney transplantation is the recipient body’s immune rejection of the transplanted organ. T -cells and antibodies attack the organ, which in the worst case can lead to graft failure. Biopsy is an important diagnostic tool to evaluate a rejection episode. TBase© includes a biopsy protocol that can easily be filled out by the physician, which helped to collect and store 1447 biopsy cases in the TBase© database. With respect to different kinds of rejections, there exist some basic rules for the entered data that are enforced during completion of the protocol. Nevertheless, because so much biopsy data was entered in by hand, it was necessary to check the quality and plausibility of existing data with respect to more complex rules that were not enforced during protocol completion. In this paper, we present the process of checking the biopsy data for consistency with complex rules provided by an expert, as well as mining of new rules using interpretable rule-based classification methods. We discovered interesting rules and relationships between features with respect to T-cell mediated rejection (TCMR), antibody-mediated rejection (AMR), interstitial fibrosis and tubular atrophy (IF/TA), and polyoma virus (BKV) nephropathy, with negative results concerning acute tubular necrosis (ATN). The discovered rules further support the quality and plausibility of the data, and open avenues for further research.

Keywords: Electronic patient record, nephrology, biopsy, data mining.