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 …
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 …
Organ aging signatures in the plasma proteome track health and disease
Animal studies show aging varies between individuals as well as between organs within an
individual,,–, but whether this is true in humans and its effect on age-related diseases is …
individual,,–, but whether this is true in humans and its effect on age-related diseases is …
Longitudinal assessment of mental health disorders and comorbidities across 4 decades among participants in the Dunedin birth cohort study
Importance Mental health professionals typically encounter patients at 1 point in patients'
lives. This cross-sectional window understandably fosters focus on the current presenting …
lives. This cross-sectional window understandably fosters focus on the current presenting …
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 …
Brain age prediction using deep learning uncovers associated sequence variants
Abstract Machine learning algorithms can be trained to estimate age from brain structural
MRI. The difference between an individual's predicted and chronological age, predicted age …
MRI. The difference between an individual's predicted and chronological age, predicted age …
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 …
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
Recent critical commentaries unfavorably compare deep learning (DL) with standard
machine learning (SML) approaches for brain imaging data analysis. However, their …
machine learning (SML) approaches for brain imaging data analysis. However, their …
[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 …
Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment
The gap between chronological age (CA) and biological brain age, as estimated from
magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging …
magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging …