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Publication
Improving diagnostic models for temporomandibular disease using cost-effective variables:an analysis of the Dimitroulis Classification
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Advisor(s)
Abstract(s)
Temporomandibular disorders (TMD) are a class of degenerative musculoskeletal and neuromuscular conditions involving the temporomandibular joint (TMJ) complex and surrounding musculature. The etiology of TMD is multifactorial, including biological,environmental, social, emotional, and cognitive triggers. Due to the
complexity of the disease’s signs and symptoms, the diagnosis and correct treatment of TMD remain a challenge. The Dimitroulis classification (DC) divides TMD into five categories (DC1, DC2, . . . , DC5)
based on the degree of disease severity with an indication for treatment. The classification is based on history and physical examination and diagnostic imaging is used to access intra-articular derangements.
This process presented some subjectivity in the analysis and, has significant associated costs. The present study aims to identify variables based on patient complaints with lower associated costs and more objective, prompt, and less burdensome classification.
Description
Keywords
Dimitroulis Scale Temporomandibular disorders Logistic Regression Receiver operating characteristic curve Bidirectional stepwise method.
Citation
Geraldes, C. B., São João, R., Cardoso, H. J. & Angelo, D. F. (2023). Improving Diagnostic Models for Temporomandibular Disease Using Cost-Effective Variables: An Analysis of the Dimitroulis Classification. In I. Gomes, T. Oliveira, A. Oliveira, P. Pestana & Min Xu (Eds.), 2023 IMS International Conference on Statistics and Data Science (ICSDS) (pp. 404-406). Institute of Mathematical Statistics. https://drive.google.com/file/d/1dgWmZWom-_f6dqzooUFYQKVngJsr5Fre/view
Publisher
Institute of Mathematical Statistics