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Quantifying uncertainty in brain-predicted age using scalar-on-image quantile regression
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Palma, Marco, Tavakoli, Shahin, Brettschneider, Julia and Nichols, Thomas E. (2020) Quantifying uncertainty in brain-predicted age using scalar-on-image quantile regression. NeuroImage, 219 . 116938. doi:10.1016/j.neuroimage.2020.116938 ISSN 1053-8119.
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Official URL: https://doi.org/10.1016/j.neuroimage.2020.116938
Abstract
Prediction of subject age from brain anatomical MRI has the potential to provide a sensitive summary of brain changes, indicative of different neurodegenerative diseases. However, existing studies typically neglect the uncertainty of these predictions. In this work we take into account this uncertainty by applying methods of functional data analysis. We propose a penalised func16 tional quantile regression model of age on brain structure with cognitively normal (CN) subjects in the Alzheimer’s Disease Neuroimaging Initiative (ADNI), and use it to predict brain age in Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD) subjects. Unlike the machine learning approaches available in the literature of brain age prediction, which provide only point predictions, the outcome of our model is a prediction interval for each subject.
Item Type: | Journal Article | ||||||||||||||||||
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Subjects: | R Medicine > RC Internal medicine | ||||||||||||||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||||||||||||||
Library of Congress Subject Headings (LCSH): | Alzheimer's disease, Brain -- Aging -- Prevention, Quantile regression, Nervous system -- Degeneration | ||||||||||||||||||
Journal or Publication Title: | NeuroImage | ||||||||||||||||||
Publisher: | Elsevier | ||||||||||||||||||
ISSN: | 1053-8119 | ||||||||||||||||||
Official Date: | 1 October 2020 | ||||||||||||||||||
Dates: |
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Volume: | 219 | ||||||||||||||||||
Article Number: | 116938 | ||||||||||||||||||
DOI: | 10.1016/j.neuroimage.2020.116938 | ||||||||||||||||||
Status: | Peer Reviewed | ||||||||||||||||||
Publication Status: | Published | ||||||||||||||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||||||||||||||
Date of first compliant deposit: | 27 May 2020 | ||||||||||||||||||
Date of first compliant Open Access: | 10 June 2020 | ||||||||||||||||||
RIOXX Funder/Project Grant: |
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