H Jiang, N Lu, K Chen, L Yao, K Li, J Zhang… - Frontiers in …, 2020 - frontiersin.org
Structural magnetic resonance imaging (MRI) studies have demonstrated that the brain undergoes age-related neuroanatomical changes not only regionally but also on the …
The deviation between chronological age and age predicted using brain MRI is a putative marker of overall brain health. Age prediction based on structural MRI data shows high …
We propose a new framework for estimating neuroimaging-derived “brain-age” at a local level within the brain, using deep learning. The local approach, contrary to existing global …
L Lin, G Zhang, J Wang, M Tian, S Wu - Multimedia Tools and Applications, 2021 - Springer
Discrepancies between the estimated brain age from brain structural MRI and the chronological age have been associated with a broad spectrum of neurocognitive disorders …
S More, G Antonopoulos, F Hoffstaedter, J Caspers… - NeuroImage, 2023 - Elsevier
The difference between age predicted using anatomical brain scans and chronological age, ie, the brain-age delta, provides a proxy for atypical aging. Various data representations and …
For decades, neuroscientists have been on a quest to search for a biomarker that can help capture age-related cognitive decline. One well-known candidate is Brain Age, or a …
D Sone, I Beheshti - Journal of Personalized Medicine, 2022 - mdpi.com
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 …
Early detection of age-related diseases will greatly benefit from a model of the underlying biological aging process. In this paper, we develop a brain-age predictor by using structural …
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 …