Brain age estimation from MRI using cascade networks with ranking loss
Chronological age of healthy people is able to be predicted accurately using deep neural
networks from neuroimaging data, and the predicted brain age could serve as a biomarker …
networks from neuroimaging data, and the predicted brain age could serve as a biomarker …
Brain age prediction of healthy subjects on anatomic MRI with deep learning: Going beyond with an “explainable AI” mindset
Objectives Define a clinically usable preprocessing pipeline for MRI data Predict brain age
using various machine learning and deep learning algorithms Define Caveat against …
using various machine learning and deep learning algorithms Define Caveat against …
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 …
Regional neuroanatomic effects on brain age inferred using magnetic resonance imaging and ridge regression
The biological age of the brain differs from its chronological age (CA) and can be used as
biomarker of neural/cognitive disease processes and as predictor of mortality. Brain age …
biomarker of neural/cognitive disease processes and as predictor of mortality. Brain age …
Investigating systematic bias in brain age estimation with application to post‐traumatic stress disorders
Brain age prediction using machine‐learning techniques has recently attracted growing
attention, as it has the potential to serve as a biomarker for characterizing the typical brain …
attention, as it has the potential to serve as a biomarker for characterizing the typical brain …
Improving brain age prediction with anatomical feature attention-enhanced 3D-CNN
Y Zhang, R Xie, I Beheshti, X Liu, G Zheng… - Computers in Biology …, 2024 - Elsevier
Currently, significant progress has been made in predicting brain age from structural
Magnetic Resonance Imaging (sMRI) data using deep learning techniques. However …
Magnetic Resonance Imaging (sMRI) data using deep learning techniques. However …
Analysing race and sex bias in brain age prediction
Brain age prediction from MRI has become a popular imaging biomarker associated with a
wide range of neuropathologies. The datasets used for training, however, are often skewed …
wide range of neuropathologies. The datasets used for training, however, are often skewed …
Predicting brain age at slice level: convolutional neural networks and consequences for interpretability
Problem: Chronological aging in later life is associated with brain degeneration processes
and increased risk for disease such as stroke and dementia. With a worldwide tendency of …
and increased risk for disease such as stroke and dementia. With a worldwide tendency of …
[HTML][HTML] Estimating brain age from structural MRI and MEG data: Insights from dimensionality reduction techniques
Brain age prediction studies aim at reliably estimating the difference between the
chronological age of an individual and their predicted age based on neuroimaging data …
chronological age of an individual and their predicted age based on neuroimaging data …
A multitask deep learning model for voxel-level brain age estimation
Global brain age estimation has been used as an effective biomarker to study the correlation
between brain aging and neurological disorders. However, it fails to provide spatial …
between brain aging and neurological disorders. However, it fails to provide spatial …