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Using machine learning and an ensemble of methods to predict kidney transplant survival
We used an ensemble of statistical methods to build a model that predicts kidney transplant survival and identifies important predictive variables. The proposed model achieved better performance, measured by Harrell’s concordance index, than the Estimated Post Transplant Survival model used in the k...
Autores principales: | Mark, Ethan, Goldsman, David, Gurbaxani, Brian, Keskinocak, Pinar, Sokol, Joel |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326487/ https://www.ncbi.nlm.nih.gov/pubmed/30625130 http://dx.doi.org/10.1371/journal.pone.0209068 |
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