Developing an ensemble machine learning model for early prediction of sepsis-associated acute kidney injury

Sepsis-associated acute kidney injury (S-AKI) is very common and early prediction is beneficial. This study aiming to develop an accurate ensemble model to predict the risk of S-AKI based on easily available clinical information. Patients with sepsis from the United States (US) database Medical Info...

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Detalles Bibliográficos
Autores principales: Zhang, Luming, Wang, Zichen, Zhou, Zhenyu, Li, Shaojin, Huang, Tao, Yin, Haiyan, Lyu, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9429796/
https://www.ncbi.nlm.nih.gov/pubmed/36060071
http://dx.doi.org/10.1016/j.isci.2022.104932

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9429796/
https://www.ncbi.nlm.nih.gov/pubmed/36060071
http://dx.doi.org/10.1016/j.isci.2022.104932

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