date: 2022-08-13T07:32:18Z pdf:PDFVersion: 1.7 pdf:docinfo:title: Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain xmp:CreatorTool: Elsevier AuthoritativeDomain[2]: elsevier.com access_permission:can_print_degraded: true subject: NeuroImage, 261 (2022) 119504. doi:10.1016/j.neuroimage.2022.119504 language: English dc:format: application/pdf; version=1.7 pdf:docinfo:custom:robots: noindex pdf:docinfo:creator_tool: Elsevier access_permission:fill_in_form: true pdf:encrypted: false dc:title: Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain modified: 2022-08-13T07:32:18Z cp:subject: NeuroImage, 261 (2022) 119504. doi:10.1016/j.neuroimage.2022.119504 pdf:docinfo:custom:CrossMarkDomains[1]: sciencedirect.com robots: noindex pdf:docinfo:subject: NeuroImage, 261 (2022) 119504. doi:10.1016/j.neuroimage.2022.119504 pdf:docinfo:creator: Simon M. Hofmann meta:author: Frauke Beyer meta:creation-date: 2022-08-13T07:31:13Z pdf:docinfo:custom:CrossmarkMajorVersionDate: 2010-04-23 created: 2022-08-13T07:31:13Z access_permission:extract_for_accessibility: true Creation-Date: 2022-08-13T07:31:13Z pdf:docinfo:custom:CrossMarkDomains[2]: elsevier.com ElsevierWebPDFSpecifications: 7.0 pdf:docinfo:custom:doi: 10.1016/j.neuroimage.2022.119504 pdf:docinfo:custom:CrossmarkDomainExclusive: true Author: Frauke Beyer producer: Acrobat Distiller 10.0.0 (Windows) CrossmarkDomainExclusive: true pdf:docinfo:producer: Acrobat Distiller 10.0.0 (Windows) doi: 10.1016/j.neuroimage.2022.119504 pdf:unmappedUnicodeCharsPerPage: 0 dc:description: NeuroImage, 261 (2022) 119504. doi:10.1016/j.neuroimage.2022.119504 Keywords: "Ageing"; "Brain-age"; "Cardiovascular risk factors"; "Explainable a.i."; "Structural mri"; "deep learning" access_permission:modify_annotations: true pdf:docinfo:custom:AuthoritativeDomain[2]: elsevier.com dc:creator: Frauke Beyer description: NeuroImage, 261 (2022) 119504. doi:10.1016/j.neuroimage.2022.119504 dcterms:created: 2022-08-13T07:31:13Z Last-Modified: 2022-08-13T07:32:18Z dcterms:modified: 2022-08-13T07:32:18Z title: Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain xmpMM:DocumentID: uuid:fd8cfc10-4791-4a8b-8025-00abb91efa0c Last-Save-Date: 2022-08-13T07:32:18Z CrossMarkDomains[1]: sciencedirect.com pdf:docinfo:keywords: "Ageing"; "Brain-age"; "Cardiovascular risk factors"; "Explainable a.i."; "Structural mri"; "deep learning" pdf:docinfo:modified: 2022-08-13T07:32:18Z meta:save-date: 2022-08-13T07:32:18Z Content-Type: application/pdf X-Parsed-By: org.apache.tika.parser.DefaultParser creator: Frauke Beyer dc:language: English dc:subject: "Ageing"; "Brain-age"; "Cardiovascular risk factors"; "Explainable a.i."; "Structural mri"; "deep learning" AuthoritativeDomain[1]: sciencedirect.com pdf:docinfo:custom:AuthoritativeDomain[1]: sciencedirect.com pdf:docinfo:custom:ElsevierWebPDFSpecifications: 7.0 access_permission:assemble_document: true xmpTPg:NPages: 16 pdf:charsPerPage: 5097 access_permission:extract_content: true access_permission:can_print: true CrossMarkDomains[2]: elsevier.com meta:keyword: "Ageing"; "Brain-age"; "Cardiovascular risk factors"; "Explainable a.i."; "Structural mri"; "deep learning" access_permission:can_modify: true pdf:docinfo:created: 2022-08-13T07:31:13Z CrossmarkMajorVersionDate: 2010-04-23