Dr. Mark Fiecas

PUBHL Biostatistics Division
School of Public Health
Twin Cities
Project Title: 
Longitudinal Analysis of Neuroimaging Data

This group develops sophisticated statistical methodologies for analyzing large-scale spatio-temporal MRI or fMRI data. The statistical models they develop leverage the complexity in the data in order to extract rich information related to the phenomenon of interest. The types of statistical models include spatio-temporal models and data-driven nonparametric machine learning tools. Due to the complexity of these types of models, a large amount of computing resources is necessary in order to fit the models and assess their performance on the data. Examples of data analyzed include MRI and fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Minnesota Twin and Family Study (MTFS).

Project Investigators

Ning Dai
Dr. Mark Fiecas
Brian Hart
Jin Jin
Adam Kaplan
Jun Young Park
 
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