Sparse Functional Linear Regression with Applications to Personalized Medicine

Abstract

McKeague and Qian (2011) recently introduced a functional data-analytic approach to finding optimal treatment policies in the setting of personalized medicine based on genomic data. The policies are specified in terms of thresholds of gene expression at estimated loci along a chromosome. Methods for assessing the effectiveness of such treatment policies are described.