… not linearly related: accumulative, relative, maximal and minimal relations between … deep
relation learning for brain age estimation and there are different ways to estimate the brain age …

… A brain age estimation framework typically employs a training … together with supervised
learning (ie, a regression algorithm) … study, we highlight the use of IDPs to investigate the relation …

… First, we estimated the heritability of brain-predicted age using the predictions from … age
from brain-predicted age, using a linear regression model. Estimates of the heritability of the age-…

… learning (ML), applied to the analysis of structural imaging, have allowed addressing regression
problems such as brain age … the brain regions that governed our brain age estimation. …

… (N = 10,158, age range 18 - 97) of structural brain MRIs in a … we train a deep learning
model for brain age estimation. The … , we use the idea of a class activation map in a regression …

… -linear regression method to predict the target subject's brain age … Deep Learning was
used for comparison, as it has … In brain age estimation, we used H 2 O package in R (https://github…

… According to research using brain MRI, there is a relation … of a brain age estimation framework
has made use of a … A trained, age-group-specific regression model is used to first make an …

… RMSE) to analyze the relationship between brain age and brain tissue volumes. According
… brain age as well as for regression for brain age estimation. The classification and regression …

… with deep neural networks for brain age estimation. However… regression analysis for brain
age estimation [18]. A multimodal … the relationship between the estimated age difference (EAD) …

… on different regression algorithms in the brain age estimation … Deep learning (DL) from
raw imaging data resulted in a … The relationship between SZ and brain age estimation was …