Predicting total knee arthroplasty from ultrasonography using machine learning

OBJECTIVE: To investigate the value of ultrasonographic data in predicting total knee replacement (TKR). DESIGN: Data from the Musculoskeletal Pain in Ullensaker study (MUST) was linked to the Norwegian Arthroplasty Register to form a 5–7 year prospective cohort study of 630 persons (69% women, mean...

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Detalles Bibliográficos
Autores principales: Tiulpin, Aleksei, Saarakkala, Simo, Mathiessen, Alexander, Hammer, Hilde Berner, Furnes, Ove, Nordsletten, Lars, Englund, Martin, Magnusson, Karin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
ORIGINAL PAPER
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718281/
https://www.ncbi.nlm.nih.gov/pubmed/36474802
http://dx.doi.org/10.1016/j.ocarto.2022.100319

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9718281/
https://www.ncbi.nlm.nih.gov/pubmed/36474802
http://dx.doi.org/10.1016/j.ocarto.2022.100319

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