Abstract
A musculoskeletal disorder is a condition of the musculoskeletal system, which consists in part of it being injured continuously over time. Shoulder disorders are one of the most common musculoskeletal cases attended in primary health care services. Shoulder disorders cause pain and limit the ability to perform many routine activities, affecting about 15-25 % of the general population. Several clinical tests have been described to aid diagnosis of shoulder disorders. However, the current literature acknowledges a lack of concordance in clinical assessment, even among musculoskeletal specialists. We are working on the design of a Computer-Aided Decision Support (CADS) system for Shoulder Pain Pathology. The paper presents the results of our efforts to build a CADS system testing several classical classification paradigms, feature reduction methods (PCA) and K-means unsupervised clustering. The small database size imposes the use of robust covariance matrix estimation methods to improve the system performance. Finally, the system was evaluated by a medical specialist.
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de Ipiña, K.L., Hernández, M.C., Martínez, E., Vaquero, C. (2010). On the Design of a CADS for Shoulder Pain Pathology. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds) Hybrid Artificial Intelligence Systems. HAIS 2010. Lecture Notes in Computer Science(), vol 6076. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13769-3_62
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DOI: https://doi.org/10.1007/978-3-642-13769-3_62
Publisher Name: Springer, Berlin, Heidelberg
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