@inproceedings{9307f4755cbd4db7b010b1aeb9d7bf34,
title = "Information-theoretic characterization of blood panel predictors for brain atrophy and cognitive decline in the elderly",
abstract = "Cognitive decline in old age is tightly linked with brain atrophy, causing significant burden. It is critical to identify which biomarkers are most predictive of cognitive decline and brain atrophy in the elderly. In 566 older adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we used a novel unsupervised machine learning approach to evaluate an extensive list of more than 200 potential brain, blood and cerebrospinal fluid (CSF)-based predictors of cognitive decline. The method, called CorEx, discovers groups of variables with high multivariate mutual information and then constructs latent factors that explain these correlations. The approach produces a hierarchical structure and the predictive power of biological variables and latent factors are compared with regression. We found that a group of variables containing the well-known AD risk gene APOE and CSF tau and amyloid levels were highly correlated. This latent factor was the most predictive of cognitive decline and brain atrophy.",
keywords = "Brain, Cells \& molecules, Genes, Machine learning, Magnetic resonance imaging (MRI)",
author = "Madsen, \{Sarah K.\} and Steeg, \{Greg Ver\} and Adam Mezher and Neda Jahanshad and Nir, \{Talia M.\} and Xue Hua and Gutman, \{Boris A.\} and Aram Galstyan and Thompson, \{Paul M.\}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 ; Conference date: 16-04-2015 Through 19-04-2015",
year = "2015",
month = jul,
day = "21",
doi = "10.1109/ISBI.2015.7164035",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "980--984",
booktitle = "2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015",
address = "United States",
}