Machine learning classifiers do not improve prediction of hospitalization > 2 days after fast-track hip and knee arthroplasty compared with a classical statistical risk model

BACKGROUND AND PURPOSE: Prediction of postoperative outcomes and length of hospital stay (LOS) of patients is vital for allocation of healthcare resources. We investigated the performance of prediction models based on machinelearning algorithms compared with a previous risk stratification model usin...

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Detalles Bibliográficos
Autores principales: JOHANNESDOTTIR, Katrin B, KEHLET, Henrik, PETERSEN, Pelle B, AASVANG, Eske K, SØRENSEN, Helge B D, JØRGENSEN, Christoffer C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medical Journals Sweden, on behalf of the Nordic Orthopedic Federation 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815306/
https://www.ncbi.nlm.nih.gov/pubmed/34984485
http://dx.doi.org/10.2340/17453674.2021.843

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8815306/
https://www.ncbi.nlm.nih.gov/pubmed/34984485
http://dx.doi.org/10.2340/17453674.2021.843

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