Predicting acute kidney injury in cancer patients using heterogeneous and irregular data

How can we predict the occurrence of acute kidney injury (AKI) in cancer patients based on machine learning with serum creatinine data? Given irregular and heterogeneous clinical data, how can we make the most of it for accurate AKI prediction? AKI is a common and significant complication in cancer...

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Detalles Bibliográficos
Autores principales: Park, Namyong, Kang, Eunjeong, Park, Minsu, Lee, Hajeong, Kang, Hee-Gyung, Yoon, Hyung-Jin, Kang, U.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053162/
https://www.ncbi.nlm.nih.gov/pubmed/30024918
http://dx.doi.org/10.1371/journal.pone.0199839

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6053162/
https://www.ncbi.nlm.nih.gov/pubmed/30024918
http://dx.doi.org/10.1371/journal.pone.0199839

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