Intelligent feature selection with modified K-nearest neighbor for kidney transplanta

Intelligent feature selection with modified K-nearest neighbor for kidney transplantation prediction
Authors
Dalia M Atallah, Mohammed Badawy, Ayman El-Sayed
Publication date
2019/10/1
Journal
SN Applied Sciences
Volume
1
Issue
10
Pages
1297
Publisher
Springer International Publishing
Description
The prediction of kidney transplantation outcome is an important challenge and does not need emphasis because of the lack of available organs. Graft survival prediction is significant to help physicians to take the right decision and enhance survival rate by changing medical procedure. Also, it helps in the best choice of the existing kidney donor and the immunosuppressive management suitable for a patient. But the exact prediction of the graft survival is still not accurate despite of the advancements in this field. The purpose of our research is to design an intelligent kidney transplantation prediction method to solve the prediction problem by utilizing data mining methods. The novelty of this study is focused in presenting: (a) an integrated prediction method, (b) a new intelligent feature selection method, and (c) a modified K-nearest neighbor. Choosing the proper variables is accomplished by merging three …

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