A Nonlinear Simulation Framework Supports Adjusting for Age When Analyzing BrainAGE.

Volume: 10, Pages: 317 - 317
Published: Oct 24, 2018
Abstract
Several imaging modalities, including T1-weighted structural imaging, diffusion tensor imaging, and functional MRI can show chronological age related changes. Employing machine learning algorithms, an individual's imaging data can predict their age with reasonable accuracy. While details vary according to modality, the general strategy is to: (1) extract image-related features, (2) build a model on a training set that uses those features to...
Paper Details
Title
A Nonlinear Simulation Framework Supports Adjusting for Age When Analyzing BrainAGE.
Published Date
Oct 24, 2018
Volume
10
Pages
317 - 317
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