Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population

This project was conducted using data from the German National Cohort (NAKO) (www.nako.de). The NAKO is funded by the Federal Ministry of Education and Research (BMBF) [project funding reference numbers: 01ER1301A/B/C, 01ER1511D, and 01ER1801A/B/C/D], federal states of Germany and the Helmholtz Association, the participating universities and the institutes of the Leibniz Association. This research has been conducted using the UK Biobank Resource under Application Number 80337. MJ was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)-518480401. VKR was funded by American Heart Association Career Development Award 935176 and National Heart, Lung, and Blood Institute-K01HL168231.

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Publication Details

Journal
EBioMedicine
Published
2024-12-01
DOI
https://doi.org/10.1016/j.ebiom.2024.105467
Citations
20
Primary Topic
Nutrition and Health in Aging
Type
article
Field-Weighted Citation Impact
6.53

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article

Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population

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20 citations
EBioMedicine
Nutrition and Health in Aging
6.53
article

Deep learning-based body composition analysis from whole-body magnetic resonance imaging to predict all-cause mortality in a large western population

Henry Völzke, Susanne Rospleszcz, Robin Bülow, Fabian Bamberg, Maximilian Frederik Russe, Tobias Pischon, Michael T. Lu, Marco Reisert, Vineet K. Raghu, Thoralf Niendorf, Christopher L. Schlett, Jakob Weiss, Matthias Jung, H. Rieder, Hans-Ulrich Kauczor
article en
20 citations

Abstract

This project was conducted using data from the German National Cohort (NAKO) (www.nako.de). The NAKO is funded by the Federal Ministry of Education and Research (BMBF) [project funding reference numbers: 01ER1301A/B/C, 01ER1511D, and 01ER1801A/B/C/D], federal states of Germany and the Helmholtz Association, the participating universities and the institutes of the Leibniz Association. This research has been conducted using the UK Biobank Resource under Application Number 80337. MJ was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)-518480401. VKR was funded by American Heart Association Career Development Award 935176 and National Heart, Lung, and Blood Institute-K01HL168231.

EBioMedicineVol. 110
Harvard University (US), University of Freiburg (DE), Max Delbrück Center (DE), Heidelberg University (DE), Universitätsmedizin Greifswald (DE), University Medical Center Freiburg (DE), University Hospital Heidelberg (DE), Helmholtz Zentrum München (DE), Universität Greifswald (DE), Massachusetts General Hospital (US), German Center for Lung Research (DE)
American Heart Association, AstraZeneca, Kowa Company, Bayer HealthCare, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Siemens Healthineers, Leibniz-Gemeinschaft, National Heart, Lung, and Blood Institute
Good health and well-being
Openalex Percentile: Top 3%
Nutrition and Health in Aging
6.53
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