Parsimonious machine learning models to predict resource use in cardiac surgery across a statewide collaborative

OBJECTIVE: We sought to several develop parsimonious machine learning models to predict resource utilization and clinical outcomes following cardiac operations using only preoperative factors. METHODS: All patients undergoing coronary artery bypass grafting and/or valve operations were identified in...

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Detalles Bibliográficos
Autores principales: Verma, Arjun, Sanaiha, Yas, Hadaya, Joseph, Maltagliati, Anthony Jason, Tran, Zachary, Ramezani, Ramin, Shemin, Richard J., Benharash, Peyman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Adult: Health Policy
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510828/
https://www.ncbi.nlm.nih.gov/pubmed/36172420
http://dx.doi.org/10.1016/j.xjon.2022.04.017

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9510828/
https://www.ncbi.nlm.nih.gov/pubmed/36172420
http://dx.doi.org/10.1016/j.xjon.2022.04.017

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