Machine learning algorithm to predict mortality in critically ill patients with sepsis-associated acute kidney injury

This study aimed to establish and validate a machine learning (ML) model for predicting in-hospital mortality in patients with sepsis-associated acute kidney injury (SA-AKI). This study collected data on SA-AKI patients from 2008 to 2019 using the Medical Information Mart for Intensive Care IV. Afte...

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Detalles Bibliográficos
Autores principales: Li, Xunliang, Wu, Ruijuan, Zhao, Wenman, Shi, Rui, Zhu, Yuyu, Wang, Zhijuan, Pan, Haifeng, Wang, Deguang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10063657/
https://www.ncbi.nlm.nih.gov/pubmed/36997585
http://dx.doi.org/10.1038/s41598-023-32160-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10063657/
https://www.ncbi.nlm.nih.gov/pubmed/36997585
http://dx.doi.org/10.1038/s41598-023-32160-z

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