Utilization of interpretable machine learning model to forecast the risk of major adverse kidney events in elderly patients in critical care

Major adverse kidney events within 30 d (MAKE30) implicates poor outcomes for elderly patients in the intensive care unit (ICU). This study aimed to predict the occurrence of MAKE30 in elderly ICU patients using machine learning. The study cohort comprised 2366 elderly ICU patients admitted to the S...

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Detalles Bibliográficos
Autores principales: Wang, Lin, Duan, Shao-Bin, Yan, Ping, Luo, Xiao-Qin, Zhang, Ning-Ya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208177/
https://www.ncbi.nlm.nih.gov/pubmed/37218683
http://dx.doi.org/10.1080/0886022X.2023.2215329

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10208177/
https://www.ncbi.nlm.nih.gov/pubmed/37218683
http://dx.doi.org/10.1080/0886022X.2023.2215329

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