A perspective on brain-age estimation and its clinical promise
Brain-age estimation has gained increased attention in the neuroscientific community owing
to its potential use as a biomarker of brain health. The difference between estimated and …
to its potential use as a biomarker of brain health. The difference between estimated and …
Prediction of brain age using structural magnetic resonance imaging: A comparison of accuracy and test–retest reliability of publicly available software packages
Brain age prediction algorithms using structural magnetic resonance imaging (MRI) aim to
assess the biological age of the human brain. The difference between a person's …
assess the biological age of the human brain. The difference between a person's …
[HTML][HTML] Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease
Background “Brain-predicted age” estimates biological age from complex, nonlinear
features in neuroimaging scans. The brain age gap (BAG) between predicted and …
features in neuroimaging scans. The brain age gap (BAG) between predicted and …
Explainable brain age prediction using covariance neural networks
In computational neuroscience, there has been an increased interest in developing machine
learning algorithms that leverage brain imaging data to provide estimates of" brain age" for …
learning algorithms that leverage brain imaging data to provide estimates of" brain age" for …
Mapping the neurodevelopmental predictors of psychopathology
RJ Jirsaraie, MM Gatavins, AR Pines, S Kandala… - Molecular …, 2024 - nature.com
Neuroimaging research has uncovered a multitude of neural abnormalities associated with
psychopathology, but few prediction-based studies have been conducted during …
psychopathology, but few prediction-based studies have been conducted during …
[HTML][HTML] Brain age has limited utility as a biomarker for capturing fluid cognition in older individuals
A Tetereva, N Pat - Elife, 2024 - elifesciences.org
One well-known biomarker candidate that supposedly helps capture fluid cognition is Brain
Age, or a predicted value based on machine-learning models built to predict chronological …
Age, or a predicted value based on machine-learning models built to predict chronological …
Transferability of Covariance Neural Networks
Graph convolutional networks (GCN) leverage topology-driven graph convolutional
operations to combine information across the graph for inference tasks. In our recent work …
operations to combine information across the graph for inference tasks. In our recent work …
BrainAGE: Revisited and reframed machine learning workflow
Since the introduction of the BrainAGE method, novel machine learning methods for brain
age prediction have continued to emerge. The idea of estimating the chronological age from …
age prediction have continued to emerge. The idea of estimating the chronological age from …
[HTML][HTML] “Puberty age gap”: new method of assessing pubertal timing and its association with mental health problems
Puberty is linked to mental health problems during adolescence, and in particular, the timing
of puberty is thought to be an important risk factor. This study developed a new measure of …
of puberty is thought to be an important risk factor. This study developed a new measure of …
[HTML][HTML] Examining the reliability of brain age algorithms under varying degrees of participant motion
JL Hanson, DJ Adkins, E Bacas, P Zhou - Brain Informatics, 2024 - Springer
Brain age algorithms using data science and machine learning techniques show promise as
biomarkers for neurodegenerative disorders and aging. However, head motion during MRI …
biomarkers for neurodegenerative disorders and aging. However, head motion during MRI …