Predicting Mortality Using Machine Learning Algorithms in Patients Who Require Renal Replacement Therapy in the Critical Care Unit

Background: General severity of illness scores are not well calibrated to predict mortality among patients receiving renal replacement therapy (RRT) for acute kidney injury (AKI). We developed machine learning models to make mortality prediction and compared their performance to that of the Sequenti...

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Detalles Bibliográficos
Autores principales: Chang, Hsin-Hsiung, Chiang, Jung-Hsien, Wang, Chi-Shiang, Chiu, Ping-Fang, Abdel-Kader, Khaled, Chen, Huiwen, Siew, Edward D., Yabes, Jonathan, Murugan, Raghavan, Clermont, Gilles, Palevsky, Paul M., Jhamb, Manisha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500742/
https://www.ncbi.nlm.nih.gov/pubmed/36142936
http://dx.doi.org/10.3390/jcm11185289

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9500742/
https://www.ncbi.nlm.nih.gov/pubmed/36142936
http://dx.doi.org/10.3390/jcm11185289

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