Machine learning for brain age prediction: Introduction to methods and clinical applications
The rise of machine learning has unlocked new ways of analysing structural neuroimaging
data, including brain age prediction. In this state-of-the-art review, we provide an …
data, including brain age prediction. In this state-of-the-art review, we provide an …
Measuring resilience and resistance in aging and Alzheimer disease using residual methods: a systematic review and meta-analysis
DI Bocancea, AC van Loenhoud, C Groot, F Barkhof… - Neurology, 2021 - AAN Enterprises
Background and Objective There is a lack of consensus on how to optimally define and
measure resistance and resilience in brain and cognitive aging. Residual methods use …
measure resistance and resilience in brain and cognitive aging. Residual methods use …
[HTML][HTML] Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease
Abstract “Brain-predicted age” quantifies apparent brain age compared to normative
neuroimaging trajectories. Advanced brain-predicted age has been well established in …
neuroimaging trajectories. Advanced brain-predicted age has been well established in …
Aging faster: worry and rumination in late life are associated with greater brain age
Older adults with anxiety have lower gray matter brain volume—a component of accelerated
aging. We have previously validated a machine learning model to predict brain age, an …
aging. We have previously validated a machine learning model to predict brain age, an …
Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer's Disease and …
I Cumplido-Mayoral, M García-Prat, G Operto, C Falcon… - Elife, 2023 - elifesciences.org
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 delta) as a marker of biological brain aging. Accelerated aging has been found in …
BrainAGE, brain health, and mental disorders: A systematic review
The imaging-based method of brainAGE aims to characterize an individual's vulnerability to
age-related brain changes. The present study systematically reviewed brainAGE findings in …
age-related brain changes. The present study systematically reviewed brainAGE findings in …
Brain-predicted age difference is associated with cognitive processing in later-life
Brain age is a neuroimaging-based biomarker of aging. This study examined whether the
difference between brain age and chronological age (brain-PAD) is associated with …
difference between brain age and chronological age (brain-PAD) is associated with …
Neuroimaging-based brain age estimation: A promising personalized biomarker in neuropsychiatry
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 …
models. This validated technique has opened up new avenues for addressing clinical …
Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction
We previously developed a novel machine-learning-based brain age model that was
sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility …
sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility …
“Brain age” predicts disability accumulation in multiple sclerosis
Objective Neurodegenerative conditions often manifest radiologically with the appearance
of premature aging. Multiple sclerosis (MS) biomarkers related to lesion burden are well …
of premature aging. Multiple sclerosis (MS) biomarkers related to lesion burden are well …