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 …
Accelerating research on biological aging and mental health: Current challenges and future directions
Aging is associated with complex biological changes that can be accelerated, slowed, or
even temporarily reversed by biological and non-biological factors. This article focuses on …
even temporarily reversed by biological and non-biological factors. This article focuses on …
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 …
Brain-age prediction: A systematic comparison of machine learning workflows
S More, G Antonopoulos, F Hoffstaedter, J Caspers… - NeuroImage, 2023 - Elsevier
The difference between age predicted using anatomical brain scans and chronological age,
ie, the brain-age delta, provides a proxy for atypical aging. Various data representations and …
ie, the brain-age delta, provides a proxy for atypical aging. Various data representations and …
Detect and correct bias in multi-site neuroimaging datasets
The desire to train complex machine learning algorithms and to increase the statistical
power in association studies drives neuroimaging research to use ever-larger datasets. The …
power in association studies drives neuroimaging research to use ever-larger datasets. The …
Brain age prediction: A comparison between machine learning models using region‐and voxel‐based morphometric data
L Baecker, J Dafflon, PF Da Costa… - Human brain …, 2021 - Wiley Online Library
Brain morphology varies across the ageing trajectory and the prediction of a person's age
using brain features can aid the detection of abnormalities in the ageing process. Existing …
using brain features can aid the detection of abnormalities in the ageing process. Existing …
Brain-predicted age difference score is related to specific cognitive functions: a multi-site replication analysis
Brain-predicted age difference scores are calculated by subtracting chronological age from
'brain'age, which is estimated using neuroimaging data. Positive scores reflect accelerated …
'brain'age, which is estimated using neuroimaging data. Positive scores reflect accelerated …
Estimating brain age based on a uniform healthy population with deep learning and structural magnetic resonance imaging
Numerous studies have established that estimated brain age constitutes a valuable
biomarker that is predictive of cognitive decline and various neurological diseases. In this …
biomarker that is predictive of cognitive decline and various neurological diseases. In this …
[HTML][HTML] Fetal brain age estimation and anomaly detection using attention-based deep ensembles with uncertainty
MRI-based brain age prediction has been widely used to characterize normal brain
development, and deviations from the typical developmental trajectory are indications of …
development, and deviations from the typical developmental trajectory are indications of …
Deep relation learning for regression and its application to brain age estimation
Most deep learning models for temporal regression directly output the estimation based on
single input images, ignoring the relationships between different images. In this paper, we …
single input images, ignoring the relationships between different images. In this paper, we …