Predicting Alzheimer's Disease Risk from Phenotypic Data and Environmental
Information
 
   Lead Investigator:    Heather Issen
   Institution      :    University of Pennsylvania
   E-Mail           :    heather.issen@pennmedicine.upenn.edu
   Proposal ID      :    1567



   Proposal Description:
   The goal of this project is to evaluate how various Machine Learning algorithms on phenotypic data perform in predicting a person's likelihood of an Alzheimer's Disease diagnosis. The objectives include identifying the phenotype variables that hold the most predicting power and to model the AD diagnosis risk using various algorithms (clustering, regression, etc.). I currently analyze a smaller subset of phenotype data using simple comparisons but want to investigate how a larger dataset and more complex algorithms can gain additional insight into AD risk.