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Predicting acute clinical deterioration with interpretable machine learning to support emergency care decision making
The emergency department (ED) is a fast-paced environment responsible for large volumes of patients with varied disease acuity. Operational pressures on EDs are increasing, which creates the imperative to efficiently identify patients at imminent risk of acute deterioration. The aim of this study is...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10442440/ https://www.ncbi.nlm.nih.gov/pubmed/37604974 http://dx.doi.org/10.1038/s41598-023-40661-0 |