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Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy
BACKGROUND: There are many Machine Learning (ML) models which predict acute kidney injury (AKI) for hospitalised patients. While a primary goal of these models is to support clinical decision-making, the adoption of inconsistent methods of estimating baseline serum creatinine (sCr) may result in a p...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BioMed Central
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10563357/ https://www.ncbi.nlm.nih.gov/pubmed/37814311 http://dx.doi.org/10.1186/s12911-023-02306-0 |