Interpretable machine learning models for predicting venous thromboembolism in the intensive care unit: an analysis based on data from 207 centers

BACKGROUND: Venous thromboembolism (VTE) is a severe complication in critically ill patients, often resulting in death and long-term disability and is one of the major contributors to the global burden of disease. This study aimed to construct an interpretable machine learning (ML) model for predict...

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Detalles Bibliográficos
Autores principales: Guan, Chengfu, Ma, Fuxin, Chang, Sijie, Zhang, Jinhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598960/
https://www.ncbi.nlm.nih.gov/pubmed/37875995
http://dx.doi.org/10.1186/s13054-023-04683-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10598960/
https://www.ncbi.nlm.nih.gov/pubmed/37875995
http://dx.doi.org/10.1186/s13054-023-04683-4

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