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Utilizing imbalanced electronic health records to predict acute kidney injury by ensemble learning and time series model
BACKGROUND: Acute Kidney Injury (AKI) is a shared complication among Intensive Care Unit (ICU), marked by high cost, high morbidity and high mortality. As the early prediction of AKI is critical for patients’ outcomes and data mining is such a powerful prediction tool, many AKI prediction models bas...
| Autores principales: | , , , , , |
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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/PMC7507620/ https://www.ncbi.nlm.nih.gov/pubmed/32957977 http://dx.doi.org/10.1186/s12911-020-01245-4 |