Abstract

As Alzheimer’s disease progresses, there are changes in metrics of brain atrophy and network breakdown derived from anatomical or diffusion MRI. Neuroimaging biomarkers of cognitive decline are crucial to identify, but few studies have investigated how sets of biomarkers cluster in terms of the information they provide. Here, we evaluated more than 700 frequently studied diffusion and anatomical measures in 247 elderly participants from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used a novel unsupervised machine learning technique - CorEx - to identify groups of measures with high multivariate mutual information; we computed latent factors to explain correlations among them. We visualized groups of measures discovered by CorEx in a hierarchical structure and determined how well they predict cognitive decline. Clusters of variables significantly predicted cognitive decline …

Date

December 8, 2025

Authors

Madelaine Daianu, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M Nir, Xiaoran Yan, Gautam Prasad, Kristina Lerman, Aram Galstyan, Paul M Thompson

Conference

Medical Computer Vision: Algorithms for Big Data: International Workshop, MCV 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 9, 2015, Revised Selected Papers 18

Pages

13-23

Publisher

Springer International Publishing