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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...

詳細記述

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書誌詳細
出版年:Crit Care
主要な著者: Zhang, Zhongheng, Ho, Kwok M., Hong, Yucai
フォーマット: Artigo
言語:Inglês
出版事項: BioMed Central 2019
主題:
オンライン・アクセス: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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