Comparable performance of machine learning algorithms in predicting readmission and complications following total joint arthroplasty with external validation

BACKGROUND: The purpose of the study was to use Machine Learning (ML) to construct a risk calculator for patients who undergo Total Joint Arthroplasty (TJA) on the basis of New York State Statewide Planning and Research Cooperative System (SPARCS) data and externally validate the calculator on a sin...

Descripción completa

Detalles Bibliográficos
Autores principales: Shaikh, Hashim J. F., Botros, Mina, Ramirez, Gabriel, Thirukumaran, Caroline P., Ricciardi, Benjamin, Myers, Thomas G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631030/
https://www.ncbi.nlm.nih.gov/pubmed/37941068
http://dx.doi.org/10.1186/s42836-023-00208-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10631030/
https://www.ncbi.nlm.nih.gov/pubmed/37941068
http://dx.doi.org/10.1186/s42836-023-00208-0

Ejemplares similares