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Estimating Patient’s Length of Stay in the Emergency Department with an Artificial Neural Network
Predicting a patient’s expected length of stay for an Emergency Department encounter is valuable to anticipate impending operational bottlenecks that may lead to diversion. We developed and validated an artificial neural network using data from >16,000 patients using clinical and operational para...
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| Main Authors: | , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
American Medical Informatics Association
2005
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC1560706/ https://ncbi.nlm.nih.gov/pubmed/16779441 |
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