Using machine learning methods to predict nonhome discharge after elective total shoulder arthroplasty

BACKGROUND: Machine learning has shown potential in accurately predicting outcomes after orthopedic surgery, thereby allowing for improved patient selection, risk stratification, and preoperative planning. This study sought to develop machine learning models to predict nonhome discharge after total...

Descripción completa

Detalles Bibliográficos
Autores principales: Lopez, Cesar D., Constant, Michael, Anderson, Matthew J.J., Confino, Jamie E., Heffernan, John T., Jobin, Charles M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Shoulder
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245980/
https://www.ncbi.nlm.nih.gov/pubmed/34223417
http://dx.doi.org/10.1016/j.jseint.2021.02.011

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8245980/
https://www.ncbi.nlm.nih.gov/pubmed/34223417
http://dx.doi.org/10.1016/j.jseint.2021.02.011

Ejemplares similares