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...

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Detalles Bibliográficos
Autores principales: Kang, Min Woo, Kim, Jayoun, Kim, Dong Ki, Oh, Kook-Hwan, Joo, Kwon Wook, Kim, Yon Su, Han, Seung Seok
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research
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

Internet

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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