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Predicting patient-reported outcomes following hip and knee replacement surgery using supervised machine learning
116
Zitationen
3
Autoren
2019
Jahr
Abstract
Supervised machine-learning implementations, like extreme gradient boosting, can provide better performance than linear models and should be considered, when high predictive performance is needed. Preoperative VAS, Q score and specific dimensions like limping are the most important predictors for postoperative hip and knee PROMs.
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