Identification of key predictors of hospital mortality in critically ill patients with embolic stroke using machine learning

Embolic stroke (ES) is characterized by high morbidity and mortality. Its mortality predictors remain unclear. The present study aimed to use machine learning (ML) to identify the key predictors of mortality for ES patients in the intensive care unit (ICU). Data were extracted from two large ICU dat...

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Detalles Bibliográficos
Autores principales: Liu, Wei, Ma, Wei, Bai, Na, Li, Chunyan, Liu, Kuangpin, Yang, Jinwei, Zhang, Sijia, Zhu, Kewei, Zhou, Qiang, Liu, Hua, Guo, Jianhui, Li, Liyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Portland Press Ltd. 2022
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484010/
https://www.ncbi.nlm.nih.gov/pubmed/35993194
http://dx.doi.org/10.1042/BSR20220995

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484010/
https://www.ncbi.nlm.nih.gov/pubmed/35993194
http://dx.doi.org/10.1042/BSR20220995

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