Deep neural networks learn general and clinically relevant representations of the ageing brain
Deep neural networks learn general and clinically relevant representations of the ageing brain
About this item
Full title
Author / Creator
Leonardsen, Esten H. , Peng, Han , Kaufmann, Tobias , Agartz, Ingrid , Andreassen, Ole A. , Celius, Elisabeth Gulowsen , Espeseth, Thomas , Harbo, Hanne F. , Høgestøl, Einar A. , Lange, Ann-Marie de , Marquand, Andre F. , Vidal-Piñeiro, Didac , Roe, James M. , Selbæk, Geir , Sørensen, Øystein , Smith, Stephen M. , Westlye, Lars T. , Wolfers, Thomas and Wang, Yunpeng
Publisher
United States: Elsevier Inc
Journal title
Language
English
Formats
Publication information
Publisher
United States: Elsevier Inc
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Scope and Contents
Contents
•Brain age CNNs achieve state-of-the-art performance in a large, multisite dataset.•A regression-based architecture outperform others in generalizing to new scanners.•Deviations in brain age associate with plausible biological and lifestyle variables.•Encoded representations are better predictors for disorder than the brain age delta.
The discre...
Alternative Titles
Full title
Deep neural networks learn general and clinically relevant representations of the ageing brain
Authors, Artists and Contributors
Author / Creator
Peng, Han
Kaufmann, Tobias
Agartz, Ingrid
Andreassen, Ole A.
Celius, Elisabeth Gulowsen
Espeseth, Thomas
Harbo, Hanne F.
Høgestøl, Einar A.
Lange, Ann-Marie de
Marquand, Andre F.
Vidal-Piñeiro, Didac
Roe, James M.
Selbæk, Geir
Sørensen, Øystein
Smith, Stephen M.
Westlye, Lars T.
Wolfers, Thomas
Wang, Yunpeng
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_40a26a731299428dbed3ac91ab54493b
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_40a26a731299428dbed3ac91ab54493b
Other Identifiers
ISSN
1053-8119,1095-9572
E-ISSN
1095-9572
DOI
10.1016/j.neuroimage.2022.119210
