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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...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2023
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| Materias: | |
| 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 |