Statistical methods for large and complex databases of ultra-high-dimensional
Description: PUBLIC HEALTH RELEVANCE: This project involves the development of statistical frameworks and methods for the analysis of complex ultra-high-dimensional biomedical imaging. Methods developed are applied to study the clinical management and etiology of multiple sclerosis and Alzheimer's disease longitudinally and cross-sectionally.
Funding type: research
Funder scheme: R01
Start date: 2013-09-28
End date: 2019-07-31
Investigator: RUSSELL TAKESHI SHINOHARA
Institution: UNIVERSITY OF PENNSYLVANIA
Funded outputs count: 152
Funder award ID: R01NS085211
OpenAlex ID: G1960095986