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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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Bibliografski detalji
Glavni autori: Wrenn, Jesse, Jones, Ian, Lanaghan, Kevin, Congdon, Clare Bates, Aronsky, Dominik
Format: Artigo
Jezik:Inglês
Izdano: American Medical Informatics Association 2005
Teme:
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC1560706/
https://ncbi.nlm.nih.gov/pubmed/16779441
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