An Explainable Machine-Learning Model for Compensatory Reserve Measurement: Methods for Feature Selection and the Effects of Subject Variability

Tracking vital signs accurately is critical for triaging a patient and ensuring timely therapeutic intervention. The patient’s status is often clouded by compensatory mechanisms that can mask injury severity. The compensatory reserve measurement (CRM) is a triaging tool derived from an arterial wave...

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Detalles Bibliográficos
Autores principales: Bedolla, Carlos N., Gonzalez, Jose M., Vega, Saul J., Convertino, Víctor A., Snider, Eric J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215239/
https://www.ncbi.nlm.nih.gov/pubmed/37237682
http://dx.doi.org/10.3390/bioengineering10050612

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10215239/
https://www.ncbi.nlm.nih.gov/pubmed/37237682
http://dx.doi.org/10.3390/bioengineering10050612

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