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Machine learning algorithm to predict mortality in patients undergoing continuous renal replacement therapy
BACKGROUND: Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately predict mortality of patients undergoing continuous renal replacement therapy (CRRT) for seve...
Autores principales: | Kang, Min Woo, Kim, Jayoun, Kim, Dong Ki, Oh, Kook-Hwan, Joo, Kwon Wook, Kim, Yon Su, Han, Seung Seok |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7006166/ https://www.ncbi.nlm.nih.gov/pubmed/32028984 http://dx.doi.org/10.1186/s13054-020-2752-7 |
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