Prediction of Acute Kidney Injury With a Machine Learning Algorithm Using Electronic Health Record Data

BACKGROUND: A major problem in treating acute kidney injury (AKI) is that clinical criteria for recognition are markers of established kidney damage or impaired function; treatment before such damage manifests is desirable. Clinicians could intervene during what may be a crucial stage for preventing...

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Detalles Bibliográficos
Autores principales: Mohamadlou, Hamid, Lynn-Palevsky, Anna, Barton, Christopher, Chettipally, Uli, Shieh, Lisa, Calvert, Jacob, Saber, Nicholas R., Das, Ritankar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2018
Materias:
Original Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6080076/
https://www.ncbi.nlm.nih.gov/pubmed/30094049
http://dx.doi.org/10.1177/2054358118776326

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6080076/
https://www.ncbi.nlm.nih.gov/pubmed/30094049
http://dx.doi.org/10.1177/2054358118776326

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