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A deep learning model for brain age prediction using minimally preprocessed T1w images as input

IntroductionIn the last few years, several models trying to calculate the biological brain age have been proposed based on structural magnetic resonance imaging scans (T1-weighted MRIs, T1w) using multivariate methods and machine learning. We developed and validated a convolutional neural network (C...

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Principais autores: Caroline Dartora, Anna Marseglia, Gustav Mårtensson, Gull Rukh, Junhua Dang, J-Sebastian Muehlboeck, Lars-Olof Wahlund, Rodrigo Moreno, José Barroso, Daniel Ferreira, Helgi B. Schiöth, Eric Westman, for the Alzheimer’s Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle Flagship Study of Ageing, the Japanese Alzheimer’s Disease Neuroimaging Initiative, the AddNeuroMed Consortium
Format: Artigo
Sprog:Inglês
Udgivet: Frontiers Media S.A. 2024-01-01
Serier:Frontiers in Aging Neuroscience
Fag:
brain age
neurodegeneration
normal ageing
CNN
UK Biobank
ageing prediction
Online adgang:https://www.frontiersin.org/articles/10.3389/fnagi.2023.1303036/full
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