Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex

Biological brain age prediction using machine learning on structural neuroimaging data: Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex

Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer’s disease (AD), but its validation against markers of neurodegeneration and...

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Bibliographic Details
Main Authors: Irene Cumplido-Mayoral, Marina García-Prat, Grégory Operto, Carles Falcon, Mahnaz Shekari, Raffaele Cacciaglia, Marta Milà-Alomà, Luigi Lorenzini, Silvia Ingala, Alle Meije Wink, Henk JMM Mutsaerts, Carolina Minguillón, Karine Fauria, José Luis Molinuevo, Sven Haller, Gael Chetelat, Adam Waldman, Adam J Schwarz, Frederik Barkhof, Ivonne Suridjan, Gwendlyn Kollmorgen, Anna Bayfield, Henrik Zetterberg, Kaj Blennow, Marc Suárez-Calvet, Verónica Vilaplana, Juan Domingo Gispert, ALFA study, EPAD study, ADNI study, OASIS study
Format: Article
Language:English
Published: eLife Sciences Publications Ltd 2023-04-01
Series:eLife
Subjects:
brain age prediction
neuroimaging
alzheimer's disease
Online Access:https://elifesciences.org/articles/81067

Internet

https://elifesciences.org/articles/81067

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