Learning optimal individualized intervention for the prevention of Alzheimer's
disease
 
   Lead Investigator:    Yingqi Zhao
   Institution      :    University of Wisconsin-Madison
   E-Mail           :    yqzhao@biostat.wisc.edu
   Proposal ID      :    321



   Proposal Description:
   This project aims to use NACC data set for exploring the optimal individualized   intervention in Alzheimer's disease (AD) prevention. Statistical learning methods will be utilized to identify the best strategy for preventing cognitively normal people from developing AD, which are potentially tailored according to different individuals characteristics.