The brain changes as we age and these changes are associated with functional
deterioration and neurodegenerative disease. It is vital that we better understand individual …

As our brains age, we tend to experience cognitive decline and are at greater risk of
neurodegenerative disease and dementia. Symptoms of chronic neuropsychiatric diseases …

Abstract Machine learning analysis of neuroimaging data can accurately predict
chronological age in healthy people. Deviations from healthy brain ageing have been …

Background Brain age is a biomarker that predicts chronological age using neuroimaging
features. Deviations of this predicted age from chronological age is considered a sign of age …

Objective During the natural course of multiple sclerosis (MS), the brain is exposed to aging
as well as disease effects. Brain aging can be modeled statistically; the so‐called “brain …

The level of prediction error in the brain age estimation frameworks is associated with the
authenticity of statistical inference on the basis of regression models. In this paper, we …

Background: Neuroimage analysis has made it possible to perform various anatomical
analyses of the brain regions and helps detect different brain conditions/disorders. Recently …

Chronological age of healthy people is able to be predicted accurately using deep neural
networks from neuroimaging data, and the predicted brain age could serve as a biomarker …

Brain-age can be inferred from structural neuroimaging and compared to chronological age
(brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in …

Brain age is a metric that quantifies the degree of aging of a brain based on whole-brain
anatomical characteristics. While associations between individual human brain regions and …