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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...
Autores principales: | Yue, Suru, Li, Shasha, Huang, Xueying, Liu, Jie, Hou, Xuefei, Zhao, Yumei, Niu, Dongdong, Wang, Yufeng, Tan, Wenkai, Wu, Jiayuan |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
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 |
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