DocumentCode
2131716
Title
Prediction of renal transplant rejection and acute tubular necrosis in renal transplant based on SVM
Author
Xun Li ; Yao Wang ; Chengxuan Wang ; Sanqing Hu ; Ying Xu ; Fei Han ; Jianghua Chen
Author_Institution
Inst. of Comput. Applic., Hangzhou Dianzi Univ., Hangzhou, China
fYear
2012
fDate
16-18 Oct. 2012
Firstpage
577
Lastpage
581
Abstract
Prevention and proper treatment of renal transplant rejection and acute tubular necrosis in kidney are the key to improving the long-term kidney transplant survival rate. Hence, it is important to predict the acute renal graft rejection in early stage. In recent years, there emerged some biomarkers measured through non-invasive techniques that may indicate the acute rejection. In this paper, we apply SVM method to analyze biomarkers, medullary R2* (MR2*) and cortical R2* (CR2*) in transplanted kidney, acquired through BOLD MRI for classification of patients with normally functioning kidney transplants and acute rejection in kidney, including acute allograft rejection and acute tubular necrosis. Furthermore, we use the classification model to predict the acute kidney rejection. The results show that the application of SVM in the analysis of CR2* and MR2* has its potential in prediction of acute rejection in kidney.
Keywords
biomedical MRI; diseases; kidney; patient treatment; support vector machines; BOLD MRI; SVM method; acute renal graft rejection; acute tubular necrosis; biomarker; cortical analysis; kidney transplant survival rate; magnetic resonance imaging; medullary analysis; patient classification model; renal transplant rejection; acute tubular necrosis; prediction; renal transplant rejection; support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Informatics (BMEI), 2012 5th International Conference on
Conference_Location
Chongqing
Print_ISBN
978-1-4673-1183-0
Type
conf
DOI
10.1109/BMEI.2012.6512936
Filename
6512936
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