Pancreatic Cancer Research

ResearcherRadboud University Medical CenterActive in the last 2 years

HenkJan J. Huisman

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

Matched on ORCID iD 0000-0001-6753-3221; OpenAlex author ID A5054345200. Sources: ClinicalTrials.gov.

Their work

Papers
9 (first author 0, last author 3)
Trials
1 (principal investigator on 1)
Grants
0
Labs led
1
Collaborators
16
Papers, trials and grants by year

2017: 1 trial · 2018: none · 2019: none · 2020: none · 2021: none · 2022: 3 papers · 2023: 1 paper · 2024: 1 paper · 2025: 1 paper · 2026: 3 papers

Papers 9

  1. Quantitative CT Perfusion as a prognostic biomarker for chemotherapy response in patients with pancreatic ductal adenocarcinoma. Co-author DOI 10.1007/s00261-026-05420-5↗
  2. Artificial intelligence and radiologists in pancreatic cancer detection using standard of care CT scans (PANORAMA): an international, paired, non-inferiority, … Co-author DOI 10.1016/s1470-2045(25)00567-4↗
  3. AI-assisted screening for pancreatic cancer – Authors' reply Last author DOI 10.1016/s1470-2045(26)00054-9↗
  4. End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study. Co-author DOI 10.1007/s00330-025-11694-y↗
  5. Automated Quantitative Analysis of CT Perfusion to Classify Vascular Phenotypes of Pancreatic Ductal Adenocarcinoma. Last author DOI 10.3390/cancers16030577↗
  6. Artificial Intelligence in Pancreatic Ductal Adenocarcinoma Imaging: A Commentary on Potential Future Applications. Co-author DOI 10.1053/j.gastro.2023.04.003↗
  7. Quantitative CT perfusion imaging in patients with pancreatic cancer: a systematic review. Co-author DOI 10.1007/s00261-021-03190-w↗
  8. Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography. Last author DOI 10.3390/cancers14020376↗
  9. Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging. Co-author DOI 10.3390/cancers14143498↗

Trials 1

  1. Defining a Vascular Phenotype of Pancreatic Ductal Adenocarcinoma With CT Perfusion Using Quantitative Radiomics Principal investigator NCT05669287↗

Closest collaborators

The 16 strongest of 16 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

  1. John J. Hermans · 8 shared papers, 1 shared trial, 2017–2026 · strength 2.22
  2. Natália Alves · 7 shared papers, 2022–2026 · strength 1.86
  3. Megan Schuurmans · 5 shared papers, 2022–2026 · strength 1.23
  4. T. H. Perik · 3 shared papers, 2022–2026 · strength 0.81
  5. Pierpaolo Vendittelli · 3 shared papers, 2022–2025 · strength 0.62
  6. Geke Litjens · 2 shared papers, 2022–2026 · strength 0.50
  7. Geert J. S. Litjens · 2 shared papers, 2023–2025 · strength 0.41
  8. Núria Malats Riera · 2 shared papers, 2023–2025 · strength 0.41
  9. Erwin J. M. van Geenen · 1 shared paper, 2026 · strength 0.32
  10. Martijn W.J. Stommel · 1 shared paper, 2026 · strength 0.32
  11. Nannan Xue · 1 shared paper, 2025 · strength 0.24
  12. Erik H.J.G. Aarntzen · 1 shared paper, 2022 · strength 0.19
  13. Matthias J. Löhr · 1 shared paper, 2023 · strength 0.18
  14. Caroline Sophie Verbeke · 1 shared paper, 2023 · strength 0.18
  15. David Kuang-Fu Chang · 1 shared paper, 2023 · strength 0.18
  16. Lodewijk A.A. Brosens · 1 shared trial, 2017 · strength 0.17

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.