[HTML][HTML] Ten Years of BrainAGE as a Neuroimaging Biomarker of Brain Aging: What Insights Have We Gained?
With the aging population, prevalence of neurodegenerative diseases is increasing, thus
placing a growing burden on individuals and the whole society. However, individual rates of …
placing a growing burden on individuals and the whole society. However, individual rates of …
[HTML][HTML] 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 …
Disparities in the pace of biological aging among midlife adults of the same chronological age have implications for future frailty risk and policy
Some humans age faster than others. Variation in biological aging can be measured in
midlife, but the implications of this variation are poorly understood. We tested associations …
midlife, but the implications of this variation are poorly understood. We tested associations …
Predicting age using neuroimaging: innovative brain ageing biomarkers
The brain changes as we age and these changes are associated with functional
deterioration and neurodegenerative disease. It is vital that we better understand individual …
deterioration and neurodegenerative disease. It is vital that we better understand individual …
[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 …
and can predict important future health outcomes. Most brain-age research uses structural …
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
Abstract Machine learning analysis of neuroimaging data can accurately predict
chronological age in healthy people. Deviations from healthy brain ageing have been …
chronological age in healthy people. Deviations from healthy brain ageing have been …
[HTML][HTML] Brain age predicts mortality
Age-associated disease and disability are placing a growing burden on society. However,
ageing does not affect people uniformly. Hence, markers of the underlying biological ageing …
ageing does not affect people uniformly. Hence, markers of the underlying biological ageing …
[HTML][HTML] Brain age and other bodily 'ages': implications for neuropsychiatry
As our brains age, we tend to experience cognitive decline and are at greater risk of
neurodegenerative disease and dementia. Symptoms of chronic neuropsychiatric diseases …
neurodegenerative disease and dementia. Symptoms of chronic neuropsychiatric diseases …
Predicting brain-age from multimodal imaging data captures cognitive impairment
The disparity between the chronological age of an individual and their brain-age measured
based on biological information has the potential to offer clinically relevant biomarkers of …
based on biological information has the potential to offer clinically relevant biomarkers of …
Deep learning-based brain age prediction in normal aging and dementia
Brain aging is accompanied by patterns of functional and structural change. Alzheimer's
disease (AD), a representative neurodegenerative disease, has been linked to accelerated …
disease (AD), a representative neurodegenerative disease, has been linked to accelerated …