Developing an Interpretable Machine Learning Model to Predict in-Hospital Mortality in Sepsis Patients: A Retrospective Temporal Validation Study

Background: Risk stratification plays an essential role in the decision making for sepsis management, as existing approaches can hardly satisfy the need to assess this heterogeneous population. We aimed to develop and validate a machine learning model to predict in-hospital mortality in critically i...

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Detalles Bibliográficos
Autores principales: Li, Shuhe, Dou, Ruoxu, Song, Xiaodong, Lui, Ka Yin, Xu, Jinghong, Guo, Zilu, Hu, Xiaoguang, Guan, Xiangdong, Cai, Changjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917524/
https://www.ncbi.nlm.nih.gov/pubmed/36769564
http://dx.doi.org/10.3390/jcm12030915

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9917524/
https://www.ncbi.nlm.nih.gov/pubmed/36769564
http://dx.doi.org/10.3390/jcm12030915

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