ResearcherUniversity of BonnActive in the last 2 years
Julian Alexander Luetkens
Matched on ORCID iD 0000-0002-7715-4636; OpenAlex author ID A5013965127. Sources: OpenAlex.
Their work
- Papers
- 2 (first author 0, last author 1)
- Trials
- 0
- Grants
- 0
- Labs led
- 0
- Collaborators
- 7
2024: 1 paper · 2025: 1 paper
Papers 2
- Skeletal muscle and visceral fat density are predictive imaging biomarkers for overall survival in patients with pancreatic adenocarcinoma: A retrospective mul… Co-author DOI 10.1016/j.suronc.2025.102251↗
- Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with advanced pancreatic cancer after high-inten… Last author DOI 10.1007/s00330-023-09974-6↗
Closest collaborators
The 7 strongest of 7 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.
- Sebastian Nowak · 2 shared papers, 2024–2025 · strength 0.48
- Paper Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with adv… DOI 10.1007/s00330-023-09974-6↗
- Paper Skeletal muscle and visceral fat density are predictive imaging biomarkers for overall survival in patients with pancre… DOI 10.1016/j.suronc.2025.102251↗
- Maike Theis · 2 shared papers, 2024–2025 · strength 0.48
- Paper Deep learning-based assessment of CT markers of sarcopenia and myosteatosis for outcome assessment in patients with adv… DOI 10.1007/s00330-023-09974-6↗
- Paper Skeletal muscle and visceral fat density are predictive imaging biomarkers for overall survival in patients with pancre… DOI 10.1016/j.suronc.2025.102251↗
- Milka Marinova · 1 shared paper, 2024 · strength 0.24
- Benjamin N. J. Thomson · 1 shared paper, 2025 · strength 0.24
- Hyun Soo Ko · 1 shared paper, 2025 · strength 0.24
- Peter Gibbs · 1 shared paper, 2025 · strength 0.24
- Belinda Lee · 1 shared paper, 2025 · strength 0.24
How to reach this person
A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.