Machine learning for the prediction of all-cause mortality in patients with sepsis-associated acute kidney injury during hospitalization

BACKGROUND: Sepsis-associated acute kidney injury (S-AKI) is considered to be associated with high morbidity and mortality, a commonly accepted model to predict mortality is urged consequently. This study used a machine learning model to identify vital variables associated with mortality in S-AKI pa...

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Detalles Bibliográficos
Autores principales: Zhou, Hongshan, Liu, Leping, Zhao, Qinyu, Jin, Xin, Peng, Zhangzhe, Wang, Wei, Huang, Ling, Xie, Yanyun, Xu, Hui, Tao, Lijian, Xiao, Xiangcheng, Nie, Wannian, Liu, Fang, Li, Li, Yuan, Qiongjing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Immunology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106833/
https://www.ncbi.nlm.nih.gov/pubmed/37077912
http://dx.doi.org/10.3389/fimmu.2023.1140755

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106833/
https://www.ncbi.nlm.nih.gov/pubmed/37077912
http://dx.doi.org/10.3389/fimmu.2023.1140755

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