Cargando…
A Novel, Potentially Universal Machine Learning Algorithm to Predict Complications in Total Knee Arthroplasty
BACKGROUND: There remains a lack of accurate and validated outcome-prediction models in total knee arthroplasty (TKA). While machine learning (ML) is a powerful predictive tool, determining the proper algorithm to apply across diverse data sets is challenging. AutoPrognosis (AP) is a novel method th...
Autores principales: | Devana, Sai K., Shah, Akash A., Lee, Changhee, Roney, Andrew R., van der Schaar, Mihaela, SooHoo, Nelson F. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349766/ https://www.ncbi.nlm.nih.gov/pubmed/34401416 http://dx.doi.org/10.1016/j.artd.2021.06.020 |
Ejemplares similares
-
Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Reverse Total Shoulder Arthroplasty
por: Devana, Sai K., et al.
Publicado: (2021) -
Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Primary Anatomic Total Shoulder Replacements
por: Devana, Sai K, et al.
Publicado: (2022) -
Development of a Machine Learning Algorithm for Prediction of Complications after Ankle Arthrodesis
por: Bugarin, Amador, et al.
Publicado: (2022) -
Factors That Predict Short-term Complication Rates After Total Hip Arthroplasty
por: SooHoo, Nelson F., et al.
Publicado: (2010) -
Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer
por: Lee, Changhee, et al.
Publicado: (2022)