Can minimal clinically important differences in patient reported outcome measures be predicted by machine learning in patients with total knee or hip arthroplasty? A systematic review

OBJECTIVES: To systematically review studies using machine learning (ML) algorithms to predict whether patients undergoing total knee or total hip arthroplasty achieve an improvement as high or higher than the minimal clinically important differences (MCID) in patient reported outcome measures (PROM...

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Detalles Bibliográficos
Autores principales: Langenberger, Benedikt, Thoma, Andreas, Vogt, Verena
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772225/
https://www.ncbi.nlm.nih.gov/pubmed/35045838
http://dx.doi.org/10.1186/s12911-022-01751-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772225/
https://www.ncbi.nlm.nih.gov/pubmed/35045838
http://dx.doi.org/10.1186/s12911-022-01751-7

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