A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study
出版年份 2017 全文链接
标题
A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study
作者
关键词
-
出版物
Scientific Reports
Volume 7, Issue 1, Pages -
出版商
Springer Nature
发表日期
2017-08-15
DOI
10.1038/s41598-017-08008-8
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Metabolic Acidosis and Long-Term Clinical Outcomes in Kidney Transplant Recipients
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- Superior outcomes of kidney transplantation compared with dialysis
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- Understanding the Causes of Kidney Transplant Failure: The Dominant Role of Antibody-Mediated Rejection and Nonadherence
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- Diagnosis and prevention of chronic kidney allograft loss
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- Fibrosis with Inflammation at One Year Predicts Transplant Functional Decline
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- Predicting the graft survival for heart–lung transplantation patients: An integrated data mining methodology
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- Comparison of the Predictive Performance of eGFR Formulae for Mortality and Graft Failure in Renal Transplant Recipients
- (2009) Xiang He et al. TRANSPLANTATION
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