Predicting Length of Stay using machine learning for total joint replacements performed at a rural community hospital

BACKGROUND: Predicting patient’s Length of Stay (LOS) before total joint replacement (TJR) surgery is vital for hospitals to optimally manage costs and resources. Many hospitals including in rural areas use publicly available models such as National Surgical Quality Improvement Program (NSQIP) calcu...

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Detalles Bibliográficos
Autores principales: Sridhar, Srinivasan, Whitaker, Bradley, Mouat-Hunter, Amy, McCrory, Bernadette
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648742/
https://www.ncbi.nlm.nih.gov/pubmed/36355762
http://dx.doi.org/10.1371/journal.pone.0277479

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9648742/
https://www.ncbi.nlm.nih.gov/pubmed/36355762
http://dx.doi.org/10.1371/journal.pone.0277479

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