Predicting anterior cruciate ligament failure load with T(2)* relaxometry and machine learning as a prospective imaging biomarker for revision surgery

Non-invasive methods to document healing anterior cruciate ligament (ACL) structural properties could potentially identify patients at risk for revision surgery. The objective was to evaluate machine learning models to predict ACL failure load from magnetic resonance images (MRI) and to determine if...

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Detalles Bibliográficos
Autores principales: Flannery, Sean W., Beveridge, Jillian E., Proffen, Benedikt L., Walsh, Edward G., Kramer, Dennis E., Murray, Martha M., Kiapour, Ata M., Fleming, Braden C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981601/
https://www.ncbi.nlm.nih.gov/pubmed/36864112
http://dx.doi.org/10.1038/s41598-023-30637-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9981601/
https://www.ncbi.nlm.nih.gov/pubmed/36864112
http://dx.doi.org/10.1038/s41598-023-30637-5

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