Pancreatic cancer AI for genomics and personalized Medicine

Informazioni relative al progetto

PANCAIM

ID dell’accordo di sovvenzione: 101016851

DOI

10.3030/101016851

Progetto chiuso

Data della firma CE 4 Dicembre 2020

Data di avvio 1 Gennaio 2021

Data di completamento 30 Settembre 2025

Finanziato da

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

Costo totale

€ 8 236 378,75

Contributo UE

€ 8 236 378,75

Coordinato da

STICHTING RADBOUD UNIVERSITAIR MEDISCH CENTRUM
Netherlands

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

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

Pubblicazioni

Peer reviewed articles (13)

Automatic quantification of tumor-stroma ratio as a prognostic marker for pancreatic cancer

Autori: Pierpaolo Vendittelli, John-Melle Bokhorst, Esther M. M. Smeets, Valentyna Kryklyva, Lodewijk A. A. Brosens, Caroline Verbeke, Geert Litjens
Pubblicato in: PLOS ONE, Numero 19, 2024, Pagina/e e0301969, ISSN 1932-6203
Editore: Public Library of Science
DOI: 10.1371/journal.pone.0301969

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

Autori: Natália Alves, Joeran S. Bosma, Kiran V. Venkadesh, Colin Jacobs, Zaigham Saghir, Maarten de Rooij, John Hermans, Henkjan Huisman
Pubblicato in: Radiology, Numero 308, 2023, ISSN 0033-8419
Editore: Radiological Society of North America
DOI: 10.1148/radiol.230275

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

Autori: Megan Schuurmans, Natália Alves, Pierpaolo Vendittelli, Henkjan Huisman, John Hermans, PANCAIM Consortium
Pubblicato in: Gastroenterology, Numero Volume 165, Numero 2, 2023, Pagina/e 309-316, ISSN 1528-0012
Editore: American Gastroenterological Association
DOI: 10.1053/j.gastro.2023.04.003

Pancreatic Cancer From the Patient Perspective: The Time to Act is Now

Autori: Marianna Vitaloni, Patrick Michl, Matthias Löhr, Ali Stunt, Patrycja Rzadkowska, Eva Backman, Lama Sharara, Vitor Neves, Thomas Gruenberger, Zorana Maravic
Pubblicato in: Journal of Patient Experience, Numero 9, 2025, ISSN 2374-3735
Editore: SAGE Publications
DOI: 10.1177/23743735221112633

A fusion-based deep-learning algorithm predicts PDAC metastasis based on primary tumour CT images: a multinational study

Autori: Nannan Xue, Sergio Sabroso-Lasa, Xavier Merino, Maria Munzo-Beltran, Megan Schuurmans, Maria Olano, Lidia Estudillo, Maria Jesús Ledesma-Carbayo, Junqi Liu, Ruitai Fan, John J Hermans, Casper van Eij
Pubblicato in: Gut, Numero 74, 2025, Pagina/e 2024-2034, ISSN 0017-5749
Editore: BMJ Publishing Group
DOI: 10.1136/gutjnl-2024-334237

The DRAGON benchmark for clinical NLP

Autori: Joeran S. Bosma, Koen Dercksen, Luc Builtjes, Romain André, Christian Roest, Stefan J. Fransen, Constant R. Noordman, Mar Navarro-Padilla, Judith Lefkes, Natália Alves, Max J. J. de Grauw, Leander v
Pubblicato in: npj Digital Medicine, Numero 8, 2025, ISSN 2398-6352
Editore: Springer Science and Business Media LLC
DOI: 10.1038/s41746-025-01626-x

Can our experience with surveillance for inherited pancreatic cancer help to identify early pancreatic cancer in the general population?

Autori: J.-Matthias Löhr, Daniel Öhlund, Emma Söreskog, Emil Andersson, Miroslav Vujasinovic, Niklas Zethraeus, Malin Sund
Pubblicato in: Familial Cancer, Numero 23, 2024, Pagina/e 399-403, ISSN 1389-9600
Editore: Kluwer Academic Publishers
DOI: 10.1007/s10689-024-00363-6

Pancreatic incidentaloma: incidental findings from history towards the era of liquid biopsy

Autori: J-Matthias Löhr, Miroslav Vujasinovic, Nikolaos Kartalis, Philipp Osten
Pubblicato in: eGastroenterology, Numero 2, 2025, Pagina/e e100082, ISSN 2766-0125
Editore: BMJ
DOI: 10.1136/egastro-2024-100082

Explainable multi-omics deep clustering model reveals an important role of DNA methylation in pancreatic ductal adenocarcinoma

Autori: Alberto López, John Zobolas, Ole Christian Lingjærde, Daniel Nebdal, Thomas Fleischer, Tero Aittokallio
Pubblicato in: Nordic Machine Intelligence, Numero 4, 2024, Pagina/e 26-42, ISSN 2703-9196
Editore: University of Oslo Library
DOI: 10.5617/nmi.10584

End-to-end prognostication in pancreatic cancer by multimodal deep learning: a retrospective, multicenter study

Autori: Megan Schuurmans, Anindo Saha, Natália Alves, Pierpaolo Vendittelli, Derya Yakar, Sergio Sabroso-Lasa, Nannan Xue, Núria Malats, Henkjan Huisman, John Hermans, Geert Litjens
Pubblicato in: European Radiology, Numero 35, 2025, Pagina/e 7537-7548, ISSN 1432-1084
Editore: Springer Science and Business Media LLC
DOI: 10.1007/s00330-025-11694-y

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

Autori: Natália Alves; Megan Schuurmans; Geke Litjens; Joeran S. Bosma; John Hermans; Henkjan J. Huisman
Pubblicato in: Cancers, Numero 14(2), 376, 2022, ISSN 2072-6694
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers14020376

Mutational signature dynamics indicate SARS-CoV-2’s evolutionary capacity is driven by host antiviral molecules

Autori: Kieran D. Lamb, Martha M. Luka, Megan Saathoff, Richard J. Orton, My V. T. Phan, Matthew Cotten, Ke Yuan, David L. Robertson
Pubblicato in: PLOS Computational Biology, Numero 20, 2024, Pagina/e e1011795, ISSN 1553-7358
Editore: Public Library of Science (PLoS)
DOI: 10.1371/journal.pcbi.1011795

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

Autori: Megan Schuurmans; Natália Alves; Pierpaolo Vendittelli; Henkjan Huisman; John Hermans
Pubblicato in: Cancers, Numero 14(14), 3498, 2022, ISSN 2072-6694
Editore: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers14143498

Other (4)

Tutorial on survival modelling with omics data

Autori: Zhi Zhao, John Zobolas, Manuela Zucknick, Tero Aittokallio
Pubblicato in: 2023
Editore: Arxiv
DOI: 10.48550/arxiv.2302.12542

Deliverable D4.1: Open-source prediction algorithms beta-tested and made available in GitHub

Autori: Zobolas, John; Aittokallio, Tero
Pubblicato in: Numero 7, 2023
Editore: PANCAIM Consortium
DOI: 10.5281/zenodo.8119247

Automatic quantification of TSR as a prognostic marker for pancreatic cancer.

Autori: Pierpaolo Vendittelli, John-Melle Bokhorst, Esther Smeets, Valentyna Kryklyva, Lodewijk Brosens, Caroline Verbeke, Geert Litjens
Pubblicato in: 2023
Editore: Research Square Platform LLC
DOI: 10.21203/rs.3.rs-3307605/v1

An example Machine Learning Survival Workflow

Autori: Zobolas, John
Pubblicato in: Numero 1, 2022
Editore: Zenodo
DOI: 10.5281/zenodo.8060668

Conference proceedings (1)

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

Autori: Vendittelli, Pierpaolo; Smeets, Esther M. M.; Litjens, Geert
Pubblicato in: Proceedings of the SPIE, Volume 12039, 2022
Editore: SPIE
DOI: 10.1117/12.2611542