Limited clinical utility of a machine learning revision prediction model based on a national hip arthroscopy registry

PURPOSE: Accurate prediction of outcome following hip arthroscopy is challenging and machine learning has the potential to improve our predictive capability. The purpose of this study was to determine if machine learning analysis of the Danish Hip Arthroscopy Registry (DHAR) can develop a clinically...

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Detalles Bibliográficos
Autores principales: Martin, R. Kyle, Wastvedt, Solvejg, Lange, Jeppe, Pareek, Ayoosh, Wolfson, Julian, Lund, Bent
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Hip
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183422/
https://www.ncbi.nlm.nih.gov/pubmed/35947158
http://dx.doi.org/10.1007/s00167-022-07054-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10183422/
https://www.ncbi.nlm.nih.gov/pubmed/35947158
http://dx.doi.org/10.1007/s00167-022-07054-8

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