Background: Brain age is a promising biomarker of brain or general health. However, to
extend the metric's clinical applications, the large intra-individual varibility in age predictions …

Introduction Brain age, the estimation of a person's age from magnetic resonance imaging
(MRI) parameters, has been used as a general indicator of health. The marker requires …

Numerous studies have established that estimated brain age, as derived from statistical
models trained on healthy populations, constitutes a valuable biomarker that is predictive of …

Numerous studies have established that estimated brain age constitutes a valuable
biomarker that is predictive of cognitive decline and various neurological diseases. In this …

Deep learning has emerged as a powerful approach to constructing imaging signatures of
normal brain ageing as well as of various neuropathological processes associated with …

The calculation of so‐called “brain age” from structural MRIs has been an emerging
biomarker in aging research. Data suggests that discrepancies between chronological age …

Brain age, most commonly inferred from T1-weighted magnetic resonance images (T1w
MRI), is a robust biomarker of brain health and related diseases. Superior accuracy in brain …

The discrepancy between chronological age and the apparent age of the brain based on
neuroimaging data—the brain age delta—has emerged as a reliable marker of brain health …

An individual's brain predicted age minus chronological age (brain-PAD) obtained from
MRIs could become a biomarker of disease in research studies. However, brain age reports …

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging
biomarker for brain health; however, the underlying neural features have remained unclear …