Development of a machine learning algorithm to identify surgical candidates for hip and knee arthroplasty without in-person evaluation

INTRODUCTION: Arthroplasty care delivery is facing a growing supply–demand mismatch. To meet future demand for joint arthroplasty, systems will need to identify potential surgical candidates prior to evaluation by orthopaedic surgeons. MATERIALS AND METHODS: Retrospective review was conducted at two...

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Detalles Bibliográficos
Autores principales: Crawford, Alexander M., Karhade, Aditya V., Agaronnik, Nicole D., Lightsey, Harry M., Xiong, Grace X., Schwab, Joseph H., Schoenfeld, Andrew J., Simpson, Andrew K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Hip Arthroplasty
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008010/
https://www.ncbi.nlm.nih.gov/pubmed/36905425
http://dx.doi.org/10.1007/s00402-023-04827-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008010/
https://www.ncbi.nlm.nih.gov/pubmed/36905425
http://dx.doi.org/10.1007/s00402-023-04827-9

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