734-936-6282

Applications:
Healthcare Research
Methodologies:
Artificial Intelligence, Data Mining, Data Visualization, Databases and Data management, Image Data, Information Theory, Machine Learning, Mathematical and Statistical Modeling, Security and Privacy
Relevant Projects:

NIH, R01 DE024450, Integrative Predictors of Temporomandibular Joint Osteoarthritis


Lucia Cevidanes

Thomas and Doris Graber Professor of Dentistry, Associate Professor

School of Dentistry

We have developed and tested machine learning approaches to integrate quantitative markers for diagnosis and assessment of progression of TMJ OA, as well as extended the capabilities of 3D Slicer4 into web-based tools and disseminated open source image analysis tools. Our aims use data processing and in-depth analytics combined with learning using privileged information, integrated feature selection, and testing the performance of longitudinal risk predictors. Our long term goals are to improve diagnosis and risk prediction of TemporoMandibular Osteoarthritis in future multicenter studies.

The Spectrum of Data Science for Diagnosis of Osteoarthritis of the Temporomandibular Joint