Machine learning for the prediction of acute kidney injury in patients with sepsis

BACKGROUND: Acute kidney injury (AKI) is the most common and serious complication of sepsis, accompanied by high mortality and disease burden. The early prediction of AKI is critical for timely intervention and ultimately improves prognosis. This study aims to establish and validate predictive model...

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Detalles Bibliográficos
Autores principales: Yue, Suru, Li, Shasha, Huang, Xueying, Liu, Jie, Hou, Xuefei, Zhao, Yumei, Niu, Dongdong, Wang, Yufeng, Tan, Wenkai, Wu, Jiayuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101823/
https://www.ncbi.nlm.nih.gov/pubmed/35562803
http://dx.doi.org/10.1186/s12967-022-03364-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9101823/
https://www.ncbi.nlm.nih.gov/pubmed/35562803
http://dx.doi.org/10.1186/s12967-022-03364-0

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