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 …
Deep learning methods for estimating" brain age" from structural MRI scans
Discrepancies between the chronological age of an individual and the neuroimaging based
data driven" brain age" have been shown to be feasible biomarkers associated to a wide …
data driven" brain age" have been shown to be feasible biomarkers associated to a wide …
[HTML][HTML] Accurate brain‐age models for routine clinical MRI examinations
DA Wood, S Kafiabadi, A Al Busaidi, E Guilhem… - Neuroimage, 2022 - Elsevier
Convolutional neural networks (CNN) can accurately predict chronological age in healthy
individuals from structural MRI brain scans. Potentially, these models could be applied …
individuals from structural MRI brain scans. Potentially, these models could be applied …
Toward MR protocol-agnostic, unbiased brain age predicted from clinical-grade MRIs
PA Valdes-Hernandez, C Laffitte Nodarse… - Scientific Reports, 2023 - nature.com
The difference between the estimated brain age and the chronological age ('brain-PAD')
could become a clinical biomarker. However, most brain age models were developed for …
could become a clinical biomarker. However, most brain age models were developed for …
Probing multiple algorithms to calculate brain age: Examining reliability, relations with demographics, and predictive power
E Bacas, I Kahhalé, PR Raamana… - Human Brain …, 2023 - Wiley Online Library
The calculation of so‐called “brain age” from structural MRIs has been an emerging
biomarker in aging research. Data suggests that discrepancies between chronological age …
biomarker in aging research. Data suggests that discrepancies between chronological age …
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 …
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 …
Mind the gap: Performance metric evaluation in brain‐age prediction
Estimating age based on neuroimaging‐derived data has become a popular approach to
developing markers for brain integrity and health. While a variety of machine‐learning …
developing markers for brain integrity and health. While a variety of machine‐learning …
Predicting brain age with deep learning from raw imaging data results in a reliable and heritable biomarker
Abstract Machine learning analysis of neuroimaging data can accurately predict
chronological age in healthy people. Deviations from healthy brain ageing have been …
chronological age in healthy people. Deviations from healthy brain ageing have been …
[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 …