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Machine Learning Outperforms Logistic Regression Analysis to Predict Next-Season NHL Player Injury: An Analysis of 2322 Players From 2007 to 2017
BACKGROUND: The opportunity to quantitatively predict next-season injury risk in the National Hockey League (NHL) has become a reality with the advent of advanced computational processors and machine learning (ML) architecture. Unlike static regression analyses that provide a momentary prediction, M...
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| Yayımlandı: | Orthop J Sports Med |
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| Asıl Yazarlar: | , , , , , , , , |
| Materyal Türü: | Artigo |
| Dil: | Inglês |
| Baskı/Yayın Bilgisi: |
SAGE Publications
2020
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| Konular: | |
| Online Erişim: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7522848/ https://ncbi.nlm.nih.gov/pubmed/33029545 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1177/2325967120953404 |
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