A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study

Accurate prediction of graft survival after kidney transplant is limited by the complexity and heterogeneity of risk factors influencing allograft survival. In this study, we applied machine learning methods, in combination with survival statistics, to build new prediction models of graft survival t...

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Detalles Bibliográficos
Autores principales: Yoo, Kyung Don, Noh, Junhyug, Lee, Hajeong, Kim, Dong Ki, Lim, Chun Soo, Kim, Young Hoon, Lee, Jung Pyo, Kim, Gunhee, Kim, Yon Su
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5567098/
https://www.ncbi.nlm.nih.gov/pubmed/28827646
http://dx.doi.org/10.1038/s41598-017-08008-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5567098/
https://www.ncbi.nlm.nih.gov/pubmed/28827646
http://dx.doi.org/10.1038/s41598-017-08008-8

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