Development and Validation of Machine Learning Models for Real-Time Mortality Prediction in Critically Ill Patients With Sepsis-Associated Acute Kidney Injury

BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is common in critically ill patients, which is associated with significantly increased mortality. Existing mortality prediction tools showed insufficient predictive power or failed to reflect patients' dynamic clinical evolution. Theref...

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Detalles Bibliográficos
Autores principales: Luo, Xiao-Qin, Yan, Ping, Duan, Shao-Bin, Kang, Yi-Xin, Deng, Ying-Hao, Liu, Qian, Wu, Ting, Wu, Xi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9240603/
https://www.ncbi.nlm.nih.gov/pubmed/35783603
http://dx.doi.org/10.3389/fmed.2022.853102

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9240603/
https://www.ncbi.nlm.nih.gov/pubmed/35783603
http://dx.doi.org/10.3389/fmed.2022.853102

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