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Predicting Rotator Cuff Tears Using Data Mining and Bayesian Likelihood Ratios
OBJECTIVES: Rotator cuff tear is a common cause of shoulder diseases. Correct diagnosis of rotator cuff tears can save patients from further invasive, costly and painful tests. This study used predictive data mining and Bayesian theory to improve the accuracy of diagnosing rotator cuff tears by clin...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2014
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986413/ https://www.ncbi.nlm.nih.gov/pubmed/24733553 http://dx.doi.org/10.1371/journal.pone.0094917 |