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User interface approaches implemented with automated patient deterioration surveillance tools: protocol for a scoping review
INTRODUCTION: Early identification of patients who may suffer from unexpected adverse events (eg, sepsis, sudden cardiac arrest) gives bedside staff valuable lead time to care for these patients appropriately. Consequently, many machine learning algorithms have been developed to predict adverse even...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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BMJ Publishing Group
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762135/ https://www.ncbi.nlm.nih.gov/pubmed/35027423 http://dx.doi.org/10.1136/bmjopen-2021-055525 |