[HTML][HTML] Morphological brain age prediction using multi-view brain networks derived from cortical morphology in healthy and disordered participants

J Corps, I Rekik - Scientific reports, 2019 - nature.com
Brain development and aging are dynamic processes that unfold over years on multiple
levels in both healthy and disordered individuals. Recent studies have revealed a disparity …

Multimodal imaging improves brain age prediction and reveals distinct abnormalities in patients with psychiatric and neurological disorders

J Rokicki, T Wolfers, W Nordhøy, N Tesli… - Human brain …, 2021 - Wiley Online Library
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 …

[HTML][HTML] Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques

A Xifra-Porxas, A Ghosh, GD Mitsis, MH Boudrias - NeuroImage, 2021 - Elsevier
Brain age prediction studies aim at reliably estimating the difference between the
chronological age of an individual and their predicted age based on neuroimaging data …

[HTML][HTML] Multimodality neuroimaging brain-age in UK biobank: relationship to biomedical, lifestyle, and cognitive factors

JH Cole - Neurobiology of aging, 2020 - Elsevier
The brain-age paradigm is proving increasingly useful for exploring aging-related disease
and can predict important future health outcomes. Most brain-age research uses structural …

[HTML][HTML] Brain age prediction: A comparison between machine learning models using brain morphometric data

J Han, SY Kim, J Lee, WH Lee - Sensors, 2022 - mdpi.com
Brain structural morphology varies over the aging trajectory, and the prediction of a person's
age using brain morphological features can help the detection of an abnormal aging …

[HTML][HTML] The vital role of central executive network in brain age: evidence from machine learning and transcriptional signatures

K Fang, S Han, Y Li, J Ding, J Wu… - Frontiers in Neuroscience, 2021 - frontiersin.org
Recent studies combining neuroimaging with machine learning methods successfully infer
an individual's brain age, and its discrepancy with the chronological age is used to identify …

[HTML][HTML] Ayu-Characterization of healthy aging from neuroimaging data with deep learning and rsfMRI

K Borkar, A Chaturvedi, PK Vinod… - Frontiers in Computational …, 2022 - frontiersin.org
Estimating brain age and establishing functional biomarkers that are prescient of cognitive
declines resulting from aging and different neurological diseases are still open research …

Connectome-based predictive models using resting-state fMRI for studying brain aging

E Kim, S Kim, Y Kim, H Cha, HJ Lee, T Lee… - Experimental Brain …, 2022 - Springer
Abstract Changes in the brain with age can provide useful information regarding an
individual's chronological age. studies have suggested that functional connectomes …

[HTML][HTML] The (limited?) utility of brain age as a biomarker for capturing cognitive decline

A Tetereva, N Pat - eLife, 2023 - elifesciences.org
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 …

[HTML][HTML] Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study

AMG De Lange, M Anatürk, S Suri, T Kaufmann… - NeuroImage, 2020 - Elsevier
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 …