Pancreatic Cancer Research

ResearcherTUM KlinikumNo recent work listed

Sebastian Ziegelmayer

ORCID-verified (high confidence, 0.95), identity_conf@1As of 8 November 2026

Matched on ORCID iD 0000-0001-8724-4718; OpenAlex author ID A5027935660. Sources: OpenAlex.

Their work

Papers
11 (first author 5, last author 0)
Trials
0
Grants
0
Labs led
0
Collaborators
20
Papers, trials and grants by year

2019: 3 papers · 2020: 3 papers · 2021: 2 papers · 2022: 2 papers · 2023: 1 paper

Papers 11

  1. CT Attenuation of Hepatic Pancreatic Cancer Metastases Correlates with Prognostically Detrimental Metastatic Necrosis. First author DOI 10.3390/jcm12237319↗
  2. Additional MRI for initial M-staging in pancreatic cancer: a cost-effectiveness analysis. First author DOI 10.1007/s00330-021-08356-0↗
  3. High-Resolution, High b-Value Computed Diffusion-Weighted Imaging Improves Detection of Pancreatic Ductal Adenocarcinoma. Co-author DOI 10.3390/cancers14030470↗
  4. [18F]FDG PET/MRI enables early chemotherapy response prediction in pancreatic ductal adenocarcinoma. Co-author DOI 10.1186/s13550-021-00808-4↗
  5. Prediction of Tumor Cellularity in Resectable PDAC from Preoperative Computed Tomography Imaging. Co-author DOI 10.3390/cancers13092069↗
  6. Image-Based Molecular Phenotyping of Pancreatic Ductal Adenocarcinoma. First author DOI 10.3390/jcm9030724↗
  7. Multiparametric Modelling of Survival in Pancreatic Ductal Adenocarcinoma Using Clinical, Histomorphological, Genetic and Image-Derived Parameters. Co-author DOI 10.3390/jcm9051250↗
  8. Deep Convolutional Neural Network-Assisted Feature Extraction for Diagnostic Discrimination and Feature Visualization in Pancreatic Ductal Adenocarcinoma (PDAC… Co-author DOI 10.3390/jcm9124013↗
  9. A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging. First author DOI 10.1186/s41747-019-0119-0↗
  10. Borderline-resectable pancreatic adenocarcinoma: Contour irregularity of the venous confluence in pre-operative computed tomography predicts histopathological … Co-author DOI 10.1371/journal.pone.0208717↗
  11. A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX … First author DOI 10.1371/journal.pone.0218642↗

Closest collaborators

The 20 strongest of 20 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

  1. Rickmer Braren · 10 shared papers, 2019–2023 · strength 1.09
  2. Fabian Karl Lohöfer · 9 shared papers, 2019–2023 · strength 0.97
  3. Georgios A. Kaissis · 8 shared papers, 2019–2021 · strength 0.79
  4. Felix N. Harder · 6 shared papers, 2020–2022 · strength 0.67
  5. Wilko Weichert · 7 shared papers, 2019–2021 · strength 0.66
  6. Friederike Jungmann · 5 shared papers, 2020–2021 · strength 0.53
  7. Roland Michael Schmid · 5 shared papers, 2019–2021 · strength 0.46
  8. Helmut Friess · 4 shared papers, 2019–2021 · strength 0.38
  9. Alexander Muckenhuber · 4 shared papers, 2019–2021 · strength 0.38
  10. Jens Thomas Siveke · 4 shared papers, 2019–2021 · strength 0.37
  11. Helmut Frieß · 3 shared papers, 2019–2021 · strength 0.28
  12. Hana Algül · 2 shared papers, 2019 · strength 0.17
  13. Stefan Reischl · 1 shared paper, 2023 · strength 0.17
  14. Matthias Frank Froelich · 1 shared paper, 2022 · strength 0.16
  15. Felix Gerhard Gassert · 1 shared paper, 2022 · strength 0.16
  16. Maximilian Reichert · 1 shared paper, 2021 · strength 0.10
  17. Michael Quante · 1 shared paper, 2021 · strength 0.10
  18. İhsan Ekin Demir · 1 shared paper, 2021 · strength 0.10
  19. Anna Melissa Schlitter · 1 shared paper, 2020 · strength 0.10
  20. Guralp Onur Ceyhan · 1 shared paper, 2019 · strength 0.09

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.