Predicting rotator cuff tears using data mining and Bayesian likelihood ratios.

Predicting rotator cuff tears using data mining and Bayesian likelihood ratios.

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 clinical examina...

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Bibliographic Details
Main Authors: Hsueh-Yi Lu, Chen-Yuan Huang, Chwen-Tzeng Su, Chen-Chiang Lin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC3986413?pdf=render

Internet

http://europepmc.org/articles/PMC3986413?pdf=render

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