Healthcare Management and Outcomes, Medical Imaging, Precision Health
Artificial Intelligence, Data Management, Data Mining, Data Security and Privacy, Data Visualization, Decision Science, Deep Learning, High-Dimensional Data Analysis, Image Data Processing and Analysis, Information Theory, Longitudinal Data Analysis, Machine Learning, Pattern Analysis and Classification, Predictive Modeling, Statistical Modeling
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