Machine learning models for predicting acute kidney injury: a systematic review and critical appraisal

BACKGROUND: The number of studies applying machine learning (ML) to predict acute kidney injury (AKI) has grown steadily over the past decade. We assess and critically appraise the state of the art in ML models for AKI prediction, considering performance, methodological soundness, and applicability....

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Detalles Bibliográficos
Autores principales: Vagliano, Iacopo, Chesnaye, Nicholas C, Leopold, Jan Hendrik, Jager, Kitty J, Abu-Hanna, Ameen, Schut, Martijn C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664575/
https://www.ncbi.nlm.nih.gov/pubmed/36381375
http://dx.doi.org/10.1093/ckj/sfac181

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9664575/
https://www.ncbi.nlm.nih.gov/pubmed/36381375
http://dx.doi.org/10.1093/ckj/sfac181

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