Predicting Renal Graft Function Post Transplantation Using Clinical and Biological Features Supported by Machine Learning Algorithms

被引：0
|
作者：
Gao, Y. [1 ]
Cui, Y. [1 ]
Kuscu, C. [2 ]
Kuscu, C. [2 ]
Gallon, L. [3 ]
Bajwa, A. [2 ]
Akalin, E. [4 ]
Eason, J. D. [2 ]
Maluf, D. [2 ]
Mas, V. [2 ]
机构：
[1] Univ Tennessee, Ctr Hlth Sci, Dept Genet, Memphis, TN 38163 USA
[2] Univ Tennessee, Ctr Hlth Sci, James D Eason Transplant Inst, Dept Surg,Transplant Res Inst, Memphis, TN 38163 USA
[3] Northwestern Univ, Chicago, IL 60611 USA
[4] Albert Einstein Coll Med, New York, NY USA
来源：
AMERICAN JOURNAL OF TRANSPLANTATION | 2020年 / 20卷
关键词：
D O I：
暂无
中图分类号：
R61 [外科手术学];
学科分类号：
摘要：
A-51
引用
收藏
页码：885 / 885
页数：1
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