… To obtain an unbiased brain age estimator and evaluate its … Ridge regression is an L2-norm
regularization linear regression … evidence of the possible relationship between different input …

… Traditional methods to estimate brain age based on 3D magnetic resonance (MR), T1 … an
end-to-end AI system based on deep learning to predict the brain age based on routine brain …

… For each regression algorithm, we applied an ensemble strategy by testing each of the
final … can be consistently used to estimate age even when datasets exhibit non-homogeneous …

… underpinnings of the ageing brain and its connection to various diseases and disorders. …
the estimated brain age of an individual we include them as inputs in the linear regression …

… After estimating brain age, a further quantity of interest is the … our deep learning model and
a well-tuned regression model, … the log-linear relationship between the training set size and …

… Finally, we estimated the age prediction performance of CNN … process regression (GPR)
and relevance vector regression (… in age prediction, similar to other deep learning research, it …

… fit brain ageing models may provide brain age estimates that are … brain age models naturally
produce brain-age estimates that … machine learning or multivariable regression techniques …

… models including deep learning. We utilize single and multimodal … their brain age estimated
from neuroimaging data. This is … regression between chronological age and brain age as a …

… In particular, brain age estimation from MRI images is a … regression was composed of 100
trees of maximum depth 15 … images, as it is difficult to integrate the spatial relationship of the …

… , Gaussian processes regression and deep neural network described in this article are …
To adjust the bias, we fitted the linear regression model of the predicted age in relation to …