Author response: 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
Year: 2023
Type: peer-review
Source: eLife
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
Institutions: Universitat Pompeu Fabra, Pasqual Maragall Foundation, Barcelonaβeta Brain Research Center, Municipal Institute for Medical Research, Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable, Hospital del Mar Research Institute, Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine, Centro de Investigación Biomédica en Red, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Institut de Recherche pour le Développement, Inserm, Physiopathologie et imagerie des troubles neurologiques, Université de Caen Normandie, UK Dementia Research Institute, University of Edinburgh, Takeda (Japan), University College London, F. Hoffmann-La Roche AG, Sahlgrenska University Hospital, UCL Queen Square Institute of Neurology, University of Gothenburg, Hospital Del Mar, Universitat Politècnica de Catalunya
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,500
OpenAlex ID: W4376483389