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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...

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Detalles Bibliográficos
Autores principales:	Lu, Xiao, Kang, Hongyu, Zhou, Dawei, Li, Qin
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2022
Materias:	Article
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

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