Development of Machine Learning Algorithms to Predict Clinically Meaningful Improvement for the Patient-Reported Health State After Total Hip Arthroplasty.
Background: Failure to achieve clinically significant outcome (CSO) improvement after total hip arthroplasty (THA) imposes a potential cost-to-risk imbalance in the context of bundle payment models. Patient perception of their health state is one component of such risk. The purpose of the current st...
| Publicado en: | Journal of Arthroplasty Vol. 35; no. 8; pp. 2119 - 2124 |
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| Autores principales: | , , , , |
| Formato: | Journal Article |
| Publicado: |
Churchill Livingstone, Inc.
Aug2020
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| Acceso en línea: | Ver este registro en EBSCOhost |