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...

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Detalles Bibliográficos
Autores principales: Lu, Hsueh-Yi, Huang, Chen-Yuan, Su, Chwen-Tzeng, Lin, Chen-Chiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Research Article
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

Internet

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

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