[HTML][HTML] Biological aging processes underlying cognitive decline and neurodegenerative disease
MM Gonzales, VR Garbarino, E Pollet… - The Journal of …, 2022 - Am Soc Clin Investig
Alzheimer's disease and related dementias (ADRD) are among the top contributors to
disability and mortality in later life. As with many chronic conditions, aging is the single most …
disability and mortality in later life. As with many chronic conditions, aging is the single most …
[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] Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan
As medical imaging enters its information era and presents rapidly increasing needs for big
data analytics, robust pooling and harmonization of imaging data across diverse cohorts …
data analytics, robust pooling and harmonization of imaging data across diverse cohorts …
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 …
MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide
Deep learning has emerged as a powerful approach to constructing imaging signatures of
normal brain ageing as well as of various neuropathological processes associated with …
normal brain ageing as well as of various neuropathological processes associated with …
A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages
Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …
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 …
Machine learning in neuroimaging: Progress and challenges
C Davatzikos - Neuroimage, 2019 - Elsevier
Conclusion The application of machine learning methods to neuroimaging has risen more
rapidly than could have been predicted 15 years ago. It has been a very exciting new …
rapidly than could have been predicted 15 years ago. It has been a very exciting new …
[HTML][HTML] A nonlinear simulation framework supports adjusting for age when analyzing BrainAGE
Several imaging modalities, including T1-weighted structural imaging, diffusion tensor
imaging, and functional MRI can show chronological age related changes. Employing …
imaging, and functional MRI can show chronological age related changes. Employing …
The Brain Chart of Aging: machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING …
Introduction Relationships between brain atrophy patterns of typical aging and Alzheimer's
disease (AD), white matter disease, cognition, and AD neuropathology were investigated via …
disease (AD), white matter disease, cognition, and AD neuropathology were investigated via …