Multiple sclerosis (MS) is an inflammatory disorder of the central nervous system. By
combining longitudinal MRI-based brain morphometry and brain age estimation using …

Background The Mayo Clinic Study of Aging is an epidemiological study of human aging.
Most MRI standard template spaces such as MNI152 are generated from scans of younger …

Brain ageing is a complex neurobiological process associated with morphological changes
that can be assessed on MRI scans. Recently, Deep learning (DL)-based approaches have …

Abstract Machine learning algorithms trained to recognize age-related structural changes in
magnetic resonance images (MRIs) of healthy individuals can be used to predict biological …

It is now possible to estimate an individual's brain age via brain scans and machine-learning
models. This validated technique has opened up new avenues for addressing clinical …

Recent studies have demonstrated that neuroimaging data can be used to estimate
biological brain age, as it captures information about the neuroanatomical and functional …

Alzheimer's disease (AD), the most common form of dementia, shares many aspects of
abnormal brain aging. We present a novel magnetic resonance imaging (MRI)-based …

Current structural MRI‐based brain age estimates and their difference from chronological
age—the brain age gap (BAG)—are limited to late‐stage pathological brain‐tissue changes …

Prediction of chronological age from neuroimaging in the healthy population is an important
issue because the deviations from normal brain age may highlight abnormal trajectories …

Brain age is becoming a widely applied imaging-based biomarker of neural aging and
potential proxy for brain integrity and health. We estimated multimodal and modality-specific …