Journal
Nature Communications
Publication Date
3-19-2025
Volume
16
Issue
1
First Page
2724
Document Type
Open Access Publication
DOI
10.1038/s41467-025-57867-7
Rights and Permissions
Govindarajan, S.T., Mamourian, E., Erus, G. et al. Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals. Nat Commun 16, 2724 (2025). https://doi.org/10.1038/s41467-025-57867-7 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Recommended Citation
Govindarajan, Sindhuja Tirumalai; Sotiras, Aristeidis; Marcus, Daniel S; LaMontagne, Pamela; Benzinger, Tammie L S; Morris, John C; and et al., "Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals." Nature Communications. 16, 1. 2724 (2025).
https://digitalcommons.wustl.edu/oa_4/5251
Department
ICTS (Institute of Clinical and Translational Sciences)
Additional Links
Supplemental material is available for this article at publisher site.
