Applying PCA-based differential identifiability to functional connectomes improves the stability and, by a modest margin, the accuracy of predicting cognitive deficits in Alzheimer's disease.
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Optimizing Differential Identifiability Improves Connectome Predictive Modeling of Cognitive Deficits in Alzheimer's Disease
Applying PCA-based differential identifiability to functional connectomes improves the stability and, by a modest margin, the accuracy of predicting cognitive deficits in Alzheimer's disease.