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Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care
BACKGROUND AND OBJECTIVES: Excess fluid balance in acute kidney injury (AKI) may be harmful, and conversely, some patients may respond to fluid challenges. This study aimed to develop a prediction model that can be used to differentiate between volume-responsive (VR) and volume-unresponsive (VU) AKI...
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| Pubblicato in: | Crit Care |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2019
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6454725/ https://ncbi.nlm.nih.gov/pubmed/30961662 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13054-019-2411-z |
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