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Machine learning for early prediction of sepsis-associated acute brain injury
BACKGROUND: Sepsis-associated encephalopathy (SAE) is defined as diffuse brain dysfunction associated with sepsis and leads to a high mortality rate. We aimed to develop and validate an optimal machine-learning model based on clinical features for early predicting sepsis-associated acute brain injur...
Autores principales: | Ge, Chenglong, Deng, Fuxing, Chen, Wei, Ye, Zhiwen, Zhang, Lina, Ai, Yuhang, Zou, Yu, Peng, Qianyi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9575145/ https://www.ncbi.nlm.nih.gov/pubmed/36262275 http://dx.doi.org/10.3389/fmed.2022.962027 |
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