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Research Group Department of Mathematics & Statistics , University at Albany , SUNY , Albany , United States
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A higher risk of Alzheimer's disease progression at baseline predicts a faster increase in brain age gap, revealing a clinically relevant stratification within at-risk populations.
The covariance eigenspace, not individual brain regions, captures the dominant longitudinal effects in brain age gap, explaining over 83% of variance between MCI subcohorts.