Pancreatic cancer AI for genomics and personalized Medicine

Project Information

PANCAIM

Grant agreement ID: 101016851

DOI 10.3030/101016851

EC signature date 4 December 2020

Start date 1 January 2021

End date 31 December 2024

Funded under

• SOCIETAL CHALLENGES - Health, demographic change and well-being

Total cost € 8 236 378,75

EU contribution € 8 236 378,75

Coordinated by

STICHTING RADBOUD UNIVERSITAIR MEDISCH CENTRUM
Netherlands

Deliverables

Websites, patent fillings, videos etc. (1)

Project webpage

Description of the PANCAIM webpage that will be prepared in the first months of the project

Other (1)

Open-source prediction algorithms beta-tested and made available in GitHub

Prediction algorithms tested by the end-user group, and the source codes of the algorithms made available for community use

Documents, reports (1)

Dissemination and communication strategy

The definition of the dissemination and communication strategy and tools to be used during the life of the project All possible dissemination routes for the obtained results will be identified and used during the whole course of the project

Publications

Peer reviewed articles (4)

Artificial Intelligence in Pancreatic Ductal Adenocarcinoma Imaging: A Commentary on Potential Future Applications

Author(s): Megan Schuurmans, Natália Alves, Pierpaolo Vendittelli, Henkjan Huisman, John Hermans, PANCAIM Consortium
Published in: Gastroenterology, Issue Volume 165, Issue 2, 2023, Page(s) 309-316, ISSN 1528-0012
Publisher: American Gastroenterological Association
DOI: 10.1053/j.gastro.2023.04.003

Prediction Variability to Identify Reduced AI Performance in Cancer Diagnosis at MRI and CT

Author(s): Natália Alves , Joeran S. Bosma, Kiran V. Venkadesh, Colin Jacobs, Zaigham Saghir, Maarten de Rooij, John Hermans, Henkjan Huisman
Published in: Radiology, Issue Volume 308, No. 3, 2023, ISSN 1527-1315
Publisher: Radiological Society of North America (RSNA)
DOI: 10.1148/radiol.230275

Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography

Author(s): Natália Alves; Megan Schuurmans; Geke Litjens; Joeran S. Bosma; John Hermans; Henkjan J. Huisman
Published in: Cancers, Issue 20726694, 2022, ISSN 2072-6694
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers14020376

Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging

Author(s): Megan Schuurmans; Natália Alves; Pierpaolo Vendittelli; Henkjan Huisman; John Hermans
Published in: Cancers, Issue 20726694, 2022, ISSN 2072-6694
Publisher: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers14143498

Other (2)

Tutorial on survival modelling with omics data

Author(s): Zhi Zhao, John Zobolas, Manuela Zucknick, Tero Aittokallio
Published in: 2023
Publisher: Arxiv
DOI: 10.48550/arxiv.2302.12542

An example Machine Learning Survival Workflow

Author(s): Zobolas, John
Published in: Issue 1, 2022
Publisher: Zenodo
DOI: 10.5281/zenodo.8060668

Conference proceedings (1)

Automatic tumour segmentation in H&E-stained whole-slide images of the pancreas.

Author(s): Vendittelli, Pierpaolo; Smeets, Esther M. M.; Litjens, Geert
Published in: Proceedings of the SPIE, Volume 12039, 2022
Publisher: SPIE
DOI: 10.1117/12.2611542