Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatini...
Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy
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London: BioMed Central Ltd
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Language
English
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London: BioMed Central Ltd
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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 poor understanding of these models' effectiveness in...
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Machine learning clinical prediction models for acute kidney injury: the impact of baseline creatinine on prediction efficacy
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TN_cdi_doaj_primary_oai_doaj_org_article_584cf1b56c7f45e58bb64a78fe233faf
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_584cf1b56c7f45e58bb64a78fe233faf
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ISSN
1472-6947
E-ISSN
1472-6947
DOI
10.1186/s12911-023-02306-0
