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Emergency department triage prediction of clinical outcomes using machine learning models
BACKGROUND: Development of emergency department (ED) triage systems that accurately differentiate and prioritize critically ill from stable patients remains challenging. We used machine learning models to predict clinical outcomes, and then compared their performance with that of a conventional appr...
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| Wydane w: | Crit Care |
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| Główni autorzy: | , , , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
BioMed Central
2019
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6387562/ https://ncbi.nlm.nih.gov/pubmed/30795786 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13054-019-2351-7 |
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