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GAUSSIAN GRAPHICAL MODELS FOR ASSESSING MULTIMODAL REGIONAL ASSOCIATIONS IN PRODROMAL ALZHEIMER’S DISEASE

      Little is known about the associations and dependencies of distinct brain lesions on a regional level, which can be assessed in vivo using various neuroimaging methods. Gaussian graphical models are a probabilistic framework that estimates the conditional dependency between individual random variables and represents them by an undirected graph. We applied this approach to study the inter-regional associations and dependencies between multimodal imaging markers in prodromal Alzheimer’s disease.
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