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Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning
Sepsis-associated encephalopathy (SAE) is a major complication of sepsis and is associated with high mortality and poor long-term prognosis. The purpose of this study is to develop interpretable machine learning models to predict the occurrence of SAE after ICU admission and implement the individual...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9805434/ https://www.ncbi.nlm.nih.gov/pubmed/36587113 http://dx.doi.org/10.1038/s41598-022-27134-6 |