Predicting older‐donor kidneys' post‐transplant renal function using pre‐transplant data

This paper provides a methodology for predicting post‐transplant kidney function, that is, the 1‐year post‐transplant estimated Glomerular Filtration Rate (eGFR‐1) for each donor‐candidate pair. We apply customized machine‐learning algorithms to pre‐transplant donor and recipient data to determine t...

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Detalles Bibliográficos
Autores principales: Martin, Paola, Gupta, Diwakar, Pruett, Timothy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Research Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108525/
https://www.ncbi.nlm.nih.gov/pubmed/37082424
http://dx.doi.org/10.1002/nav.22083

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10108525/
https://www.ncbi.nlm.nih.gov/pubmed/37082424
http://dx.doi.org/10.1002/nav.22083

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