Cargando…
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...
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: | |
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 |
Ejemplares similares
-
Machine learning algorithm to predict anterior cruciate ligament revision demonstrates external validity
por: Martin, R. Kyle, et al.
Publicado: (2022) -
Hip arthroscopy for femoroacetabular impingement
por: Nasser, Rima, et al.
Publicado: (2018) -
The current situation in hip arthroscopy
por: Marin-Peña, Oliver, et al.
Publicado: (2017) -
Adhesions in the setting of hip arthroscopy
por: Ruzbarsky, Joseph J, et al.
Publicado: (2023) -
Hip arthroscopy in the setting of hip dysplasia: A systematic review
por: Yeung, M., et al.
Publicado: (2016)