Capturing heterogeneous group differences using mixture-of-experts: Application to a study of aging.

ABSTRACT: In MRI studies, linear multi-variate methods are often employed to identify regions or connections that are affected due to disease or normal aging. Such linear models inherently assume that there is a single, homogeneous abnormality pattern that is present in all affected individuals. While kernel-based methods can implicitly model a non-linear effect, and therefore the heterogeneity in the affected group, extracting and interpreting information about affected regions is difficult. In this paper, we present a method that explicitly models and captures heterogeneous patterns of change in the affected group relative to a reference group of controls. For this purpose, we use the Mixture-of-Experts (MOE) framework, which combines unsupervised modeling of mixtures of distributions with supervi

SUBMITTER: Eavani H 

PROVIDER: S-EPMC5460911 | biostudies-literature | 2016 Jan

REPOSITORIES: biostudies-literature