A new proposed feature selection method to predict kidney transplantation outcome

A new proposed feature selection method to predict kidney transplantation outcome
Authors
Dalia M Atallah, Mohammed Badawy, Ayman El-Sayed
Publication date
2019/11/1
Journal
Health and Technology
Volume
9
Issue
5
Pages
847-856
Publisher
Springer Berlin Heidelberg
Description
Kidney transplantation graft survival prediction is important because of the difficulty of finding the organs. The exact prediction of kidney transplantation outcome is still not accurate even with the enhancements in acute rejection results. Machine learning methods introduce many ways to solve the kidney transplantation prediction problem than that of other methods. The power of any prediction method relies on the choosing of the proper variables. Feature selection is one of the important preprocessing procedures. It is the method that selects the minimal suitable variables that introduced in a set of features. This paper introduced a new proposed feature selection method that combines statistical methods with classification procedures of data mining technology to predict the probability of graft survival after kidney transplantation. Univariate analysis using Kaplan-Meier survival analysis method combined with …

ملف مرفق 1163

يمكنك الاطلاع على البحث كاملا
انظر المرفق