Age- and BMI-Dependent Psoas and Gluteus Muscle Mass in 27,805 Participants of the Population-Based German National Cohort (NAKO Gesundheitsstudie): A Deep-Learning 3T MRI Study.
Article in Diagnostics (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what money
Authors and funding
11 authors.
Lena Sophie KieferDepartment of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Hoppe-Seyler-Straße 3, 72076 Tuebingen, Germany.ORCID 0000-0002-3999-559X
Marius WinterDepartment of Diagnostic and Interventional Radiology, Eberhard Karls University of Tuebingen, 72076 Tuebingen, Germany.
Sofia PappaDepartment of Diagnostic and Interventional Radiology, Eberhard Karls University of Tuebingen, 72076 Tuebingen, Germany.
Marc FischerInstitute of Signal Processing and System Theory, University of Stuttgart, 70550 Stuttgart, Germany.
Thomas KüstnerDepartment of Diagnostic and Interventional Radiology, Eberhard Karls University of Tuebingen, 72076 Tuebingen, Germany.ORCID 0000-0002-0353-4898
Thierno D DialloDepartment of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany.
Eduardo CalderónDepartment of Nuclear Medicine and Clinical Molecular Imaging, University Hospital Tuebingen, Hoppe-Seyler-Straße 3, 72076 Tuebingen, Germany.ORCID 0009-0000-3837-7151
Fabian BambergDepartment of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, 79106 Freiburg, Germany.ORCID 0000-0002-7460-3942
Konstantin NikolaouDepartment of Diagnostic and Interventional Radiology, Eberhard Karls University of Tuebingen, 72076 Tuebingen, Germany.ORCID 0000-0003-2668-7325
Bin YangInstitute of Signal Processing and System Theory, University of Stuttgart, 70550 Stuttgart, Germany.ORCID 0000-0002-8322-117X
Fritz SchickDepartment of Diagnostic and Interventional Radiology, Eberhard Karls University of Tuebingen, 72076 Tuebingen, Germany.ORCID 0000-0002-4231-3406
Funding
DFG 4282 10203
6 · The paper itself
Abstract
PubMed holds no abstract for this paper.
Indexed as
deep learningGerman National Cohortmuscle segmentationmuscle volumeskeletal muscle mass
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Age- and BMI-Dependent Psoas and Gluteus Muscle Mass in 27,805 Participants of the Population-Based German National Cohort (NAKO Gesundheitsstudie): A Deep-Learning 3T MRI Study. · full record | OpenQuestion