Machine learning approach for the prediction of 30-day mortality in patients with sepsis-associated encephalopathy

OBJECTIVE: Our study aimed to identify predictors as well as develop machine learning (ML) models to predict the risk of 30-day mortality in patients with sepsis-associated encephalopathy (SAE). MATERIALS AND METHODS: ML models were developed and validated based on a public database named Medical In...

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Detalles Bibliográficos
Autores principales: Peng, Liwei, Peng, Chi, Yang, Fan, Wang, Jian, Zuo, Wei, Cheng, Chao, Mao, Zilong, Jin, Zhichao, Li, Weixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252033/
https://www.ncbi.nlm.nih.gov/pubmed/35787248
http://dx.doi.org/10.1186/s12874-022-01664-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252033/
https://www.ncbi.nlm.nih.gov/pubmed/35787248
http://dx.doi.org/10.1186/s12874-022-01664-z

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