Pancreatic Cancer Research

ResearcherTechnical University of MunichActive in the last 2 years

Felix N. Harder

ORCID-verified (high confidence, 0.95), identity_conf@1As of 7 November 2026

Matched on ORCID iD 0000-0002-3182-5924. Sources: OpenAlex.

Their work

Papers
9
Trials
0
Grants
0
Labs led
0
Collaborators
28
Papers, trials and grants by year

2020: 3 papers · 2021: 2 papers · 2022: 3 papers · 2023: none · 2024: none · 2025: 1 paper

Papers 9

  1. Correction to: Functional biomarkers derived from computed tomography and magnetic resonance imaging differentiate PDAC subgroups and reveal gemcitabine‑induce… Co-author DOI 10.1007/s00259-025-07195-1↗
  2. Functional biomarkers derived from computed tomography and magnetic resonance imaging differentiate PDAC subgroups and reveal gemcitabine-induced hypo-vascular… Co-author DOI 10.1007/s00259-022-05930-6↗
  3. Identification of treatment-induced vulnerabilities in pancreatic cancer patients using functional model systems. Co-author DOI 10.15252/emmm.202114876↗
  4. High-Resolution, High b-Value Computed Diffusion-Weighted Imaging Improves Detection of Pancreatic Ductal Adenocarcinoma. Co-author DOI 10.3390/cancers14030470↗
  5. [18F]FDG PET/MRI enables early chemotherapy response prediction in pancreatic ductal adenocarcinoma. Co-author DOI 10.1186/s13550-021-00808-4↗
  6. Prediction of Tumor Cellularity in Resectable PDAC from Preoperative Computed Tomography Imaging. Co-author DOI 10.3390/cancers13092069↗
  7. Image-Based Molecular Phenotyping of Pancreatic Ductal Adenocarcinoma. Co-author DOI 10.3390/jcm9030724↗
  8. Multiparametric Modelling of Survival in Pancreatic Ductal Adenocarcinoma Using Clinical, Histomorphological, Genetic and Image-Derived Parameters. Co-author DOI 10.3390/jcm9051250↗
  9. Deep Convolutional Neural Network-Assisted Feature Extraction for Diagnostic Discrimination and Feature Visualization in Pancreatic Ductal Adenocarcinoma (PDAC… Co-author DOI 10.3390/jcm9124013↗

Closest collaborators

The 25 strongest of 28 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

  1. Rickmer Braren · 9 shared papers, 2020–2025 · strength 1.10
  2. Fabian Karl Lohöfer · 7 shared papers, 2020–2025 · strength 0.86
  3. Georgios A. Kaissis · 7 shared papers, 2020–2025 · strength 0.85
  4. Wilko Weichert · 7 shared papers, 2020–2025 · strength 0.83
  5. Sebastian Ziegelmayer · 6 shared papers, 2020–2022 · strength 0.67
  6. Friederike Jungmann · 5 shared papers, 2020–2021 · strength 0.53
  7. Jens Thomas Siveke · 4 shared papers, 2020–2025 · strength 0.51
  8. Roland Michael Schmid · 4 shared papers, 2020–2022 · strength 0.40
  9. Helmut Friess · 3 shared papers, 2020–2022 · strength 0.32
  10. Lucia Liotta · 2 shared papers, 2022–2025 · strength 0.32
  11. Marija Trajkovic‐Arsic · 2 shared papers, 2022–2025 · strength 0.32
  12. Irina Heid · 2 shared papers, 2022–2025 · strength 0.32
  13. Hana Algül · 2 shared papers, 2022–2025 · strength 0.32
  14. Alexander Muckenhuber · 3 shared papers, 2020–2021 · strength 0.29
  15. Maximilian Reichert · 2 shared papers, 2021–2022 · strength 0.21
  16. İhsan Ekin Demir · 2 shared papers, 2021–2022 · strength 0.21
  17. Anna Melissa Schlitter · 2 shared papers, 2020–2022 · strength 0.21
  18. Helmut Frieß · 2 shared papers, 2020–2021 · strength 0.20
  19. Katja Peschke · 1 shared paper, 2022 · strength 0.11
  20. H. Carlo Maurer · 1 shared paper, 2022 · strength 0.11
  21. Felix Orben · 1 shared paper, 2022 · strength 0.11
  22. Sebastian Lange · 1 shared paper, 2022 · strength 0.11
  23. Christoph Schlag · 1 shared paper, 2022 · strength 0.11
  24. Roland Rad · 1 shared paper, 2022 · strength 0.11
  25. Günter Schneider · 1 shared paper, 2022 · strength 0.11

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.