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Can Machine Learning Algorithms Predict Which Patients Will Achieve Minimally Clinically Important Differences From Total Joint Arthroplasty?
BACKGROUND: Identifying patients at risk of not achieving meaningful gains in long-term postsurgical patient-reported outcome measures (PROMs) is important for improving patient monitoring and facilitating presurgical decision support. Machine learning may help automatically select and weigh many pr...
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| izdano v: | Clin Orthop Relat Res |
|---|---|
| Main Authors: | , , , , |
| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
Wolters Kluwer
2019
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| Teme: | |
| Online dostop: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6554103/ https://ncbi.nlm.nih.gov/pubmed/31094833 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/CORR.0000000000000687 |
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