Predicting the risk factors of diabetic ketoacidosis-associated acute kidney injury: A machine learning approach using XGBoost

OBJECTIVE: The purpose of this study was to develop and validate a predictive model based on a machine learning (ML) approach to identify patients with DKA at increased risk of AKI within 1 week of hospitalization in the intensive care unit (ICU). METHODS: Patients diagnosed with DKA from the Medica...

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Detalles Bibliográficos
Autores principales: Fan, Tingting, Wang, Jiaxin, Li, Luyao, Kang, Jing, Wang, Wenrui, Zhang, Chuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Public Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117643/
https://www.ncbi.nlm.nih.gov/pubmed/37089510
http://dx.doi.org/10.3389/fpubh.2023.1087297

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10117643/
https://www.ncbi.nlm.nih.gov/pubmed/37089510
http://dx.doi.org/10.3389/fpubh.2023.1087297

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