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2019 Annual Session Conference

Thomas M. Graber Award of Special Merit: Minimally Invasive Predictive Model for TMJ Osteoarthritis: Integrating Biomarkers and Machine Learning

May 6, 2019 9:40am ‐ May 6, 2019 10:00am


Is artificial intelligence redefining the gold standard for diagnosing TMJ osteoarthritis? What use to be thought of as a ‘wear and tear’ condition that leads to bone and cartilage destruction has been recently correlated with pro-inflammatory mediators. Advances in this field have led the drive to the use of biomarkers to predict future incidence or progression of osteoarthritis. The heterogeneity of individual disease progression creates challenges for prediction algorithms. A state-of-the-art machine learning technique now provides novel insights into the molecular basis of arthritis of the TMJ.

Learning Objectives:

  • Discuss the correlations among biologic and clinical markers that are associated with condylar morphological variability.
  • Compare the difference in shape variance among the five different stages of bone degeneration experienced by arthritic TMJs.
  • Evaluate the accuracy of a neural network based on the classification of the mandibular condyles of patients whom have degenerative TMJ disease.


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