Applications of deep learning techniques for automated multiple sclerosis detection using magnetic resonance imaging: A review

A Shoeibi, M Khodatars, M Jafari, P Moridian… - Computers in Biology …, 2021 - Elsevier
Multiple Sclerosis (MS) is a type of brain disease which causes visual, sensory, and motor
problems for people with a detrimental effect on the functioning of the nervous system. In …

A perspective on brain-age estimation and its clinical promise

C Gaser, P Kalc, JH Cole - Nature computational science, 2024 - nature.com
Brain-age estimation has gained increased attention in the neuroscientific community owing
to its potential use as a biomarker of brain health. The difference between estimated and …

Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images

B Zhao, T Li, Z Fan, Y Yang, J Shu, X Yang, X Wang… - Science, 2023 - science.org
Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is
known about the phenotypic and genetic links of heart-brain systems. We quantified heart …

Mind the gap: Performance metric evaluation in brain‐age prediction

AMG de Lange, M Anatürk, J Rokicki… - Human Brain …, 2022 - Wiley Online Library
Estimating age based on neuroimaging‐derived data has become a popular approach to
develo** markers for brain integrity and health. While a variety of machine‐learning …

[HTML][HTML] Deep neural networks learn general and clinically relevant representations of the ageing brain

EH Leonardsen, H Peng, T Kaufmann, I Agartz… - NeuroImage, 2022 - Elsevier
The discrepancy between chronological age and the apparent age of the brain based on
neuroimaging data—the brain age delta—has emerged as a reliable marker of brain health …

A review on brain age prediction models

LKS Kumari, R Sundarrajan - Brain Research, 2024 - Elsevier
Brain age in neuroimaging has emerged over the last decade and reflects the estimated age
based on the brain MRI scan from a person. As a person ages, their brain structure will …

A systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility

RJ Jirsaraie, AJ Gorelik, MM Gatavins, DA Engemann… - Patterns, 2023 - cell.com
Brain aging is a complex, multifaceted process that can be challenging to model in ways that
are accurate and clinically useful. One of the most common approaches has been to apply …

Prediction of brain age and cognitive age: Quantifying brain and cognitive maintenance in aging

M Anatürk, T Kaufmann, JH Cole, S Suri… - Human brain …, 2021 - Wiley Online Library
The concept of brain maintenance refers to the preservation of brain integrity in older age,
while cognitive reserve refers to the capacity to maintain cognition in the presence of …

Multimodal imaging improves brain age prediction and reveals distinct abnormalities in patients with psychiatric and neurological disorders

J Rokicki, T Wolfers, W Nordhøy, N Tesli… - Human brain …, 2021 - Wiley Online Library
The deviation between chronological age and age predicted using brain MRI is a putative
marker of overall brain health. Age prediction based on structural MRI data shows high …

[HTML][HTML] rsHRF: A toolbox for resting-state HRF estimation and deconvolution

GR Wu, N Colenbier, S Van Den Bossche, K Clauw… - NeuroImage, 2021 - Elsevier
The hemodynamic response function (HRF) greatly influences the intra-and inter-subject
variability of brain activation and connectivity, and might confound the estimation of temporal …