Personalized prediction of delayed graft function for recipients of deceased donor kidney transplants with machine learning

Machine learning (ML) has shown its potential to improve patient care over the last decade. In organ transplantation, delayed graft function (DGF) remains a major concern in deceased donor kidney transplantation (DDKT). To this end, we harnessed ML to build personalized prognostic models to predict...

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Detalles Bibliográficos
Autores principales: Kawakita, Satoru, Beaumont, Jennifer L., Jucaud, Vadim, Everly, Matthew J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591492/
https://www.ncbi.nlm.nih.gov/pubmed/33110142
http://dx.doi.org/10.1038/s41598-020-75473-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591492/
https://www.ncbi.nlm.nih.gov/pubmed/33110142
http://dx.doi.org/10.1038/s41598-020-75473-z

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