Determining an Optimal Oxygen Saturation Target Range Based on Neonatal Maturity: Demonstration of a Decision Tree Analytic

The utility of decision tree machine learning in exploring the interactions among the SpO(2) target range, neonatal maturity, and oxemic-risk is demonstrated. METHODS: This observational study used 3 years of paired age-SpO(2)-PaO(2) data from a neonatal ICU. The CHAID decision tree method was used...

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Detalles Bibliográficos
Autores principales: Bachman, Thomas E., Iyer, Narayan P., Newth, Christopher J. L., LeMoyne, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10648394/
https://www.ncbi.nlm.nih.gov/pubmed/37958208
http://dx.doi.org/10.3390/diagnostics13213312

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10648394/
https://www.ncbi.nlm.nih.gov/pubmed/37958208
http://dx.doi.org/10.3390/diagnostics13213312

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