Machine learning for the prediction of acute kidney injury in critical care patients with acute cerebrovascular disease

PURPOSE: Acute kidney injury (AKI) is a common complication and associated with a poor clinical outcome. In this study, we developed and validated a model for predicting the risk of AKI through machine learning methods in critical care patients with acute cerebrovascular disease. METHODS: This study...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaohong, Chen, Siying, Lai, Kunmei, Chen, Zhimin, Wan, Jianxin, Xu, Yanfang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2022
Materias:
Clinical Studies
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856083/
https://www.ncbi.nlm.nih.gov/pubmed/35166177
http://dx.doi.org/10.1080/0886022X.2022.2036619

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856083/
https://www.ncbi.nlm.nih.gov/pubmed/35166177
http://dx.doi.org/10.1080/0886022X.2022.2036619

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