Considerations on brain age predictions from repeatedly sampled data across time
M Korbmacher, MY Wang, R Eikeland… - Brain and …, 2023 - Wiley Online Library
Introduction Brain age, the estimation of a person's age from magnetic resonance imaging
(MRI) parameters, has been used as a general indicator of health. The marker requires …
(MRI) parameters, has been used as a general indicator of health. The marker requires …
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 …
Estimating brain age based on a healthy population with deep learning and structural MRI
Numerous studies have established that estimated brain age, as derived from statistical
models trained on healthy populations, constitutes a valuable biomarker that is predictive of …
models trained on healthy populations, constitutes a valuable biomarker that is predictive of …
[HTML][HTML] Feasibility of brain age predictions from clinical T1-weighted MRIs
PA Valdes-Hernandez, CL Nodarse, JH Cole… - Brain Research …, 2023 - Elsevier
An individual's brain predicted age minus chronological age (brain-PAD) obtained from
MRIs could become a biomarker of disease in research studies. However, brain age reports …
MRIs could become a biomarker of disease in research studies. However, brain age reports …
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 …
MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide
Deep learning has emerged as a powerful approach to constructing imaging signatures of
normal brain ageing as well as of various neuropathological processes associated with …
normal brain ageing as well as of various neuropathological processes associated with …
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 …
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 …
Optimising brain age estimation through transfer learning: A suite of pre‐trained foundation models for improved performance and generalisability in a clinical setting
Estimated age from brain MRI data has emerged as a promising biomarker of neurological
health. However, the absence of large, diverse, and clinically representative training …
health. However, the absence of large, diverse, and clinically representative training …
Brain age prediction: A comparison between machine learning models using brain morphometric data
Brain structural morphology varies over the aging trajectory, and the prediction of a person's
age using brain morphological features can help the detection of an abnormal aging …
age using brain morphological features can help the detection of an abnormal aging …