Pancreatic cancer AI for genomics and personalized Medicine

Información del proyecto

PANCAIM

Identificador del acuerdo de subvención: 101016851

DOI

10.3030/101016851

Proyecto cerrado

Fecha de la firma de la CE 4 Diciembre 2020

Fecha de inicio 1 Enero 2021

Fecha de finalización 30 Septiembre 2025

Financiado con arreglo a

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

Coste total

€ 8 236 378,75

Aportación de la UE

€ 8 236 378,75

Coordinado por

STICHTING RADBOUD UNIVERSITAIR MEDISCH CENTRUM
Netherlands

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Resultado final

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

Publicaciones

Peer reviewed articles (13)

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

Autores: Pierpaolo Vendittelli, John-Melle Bokhorst, Esther M. M. Smeets, Valentyna Kryklyva, Lodewijk A. A. Brosens, Caroline Verbeke, Geert Litjens
Publicado en: PLOS ONE, Edición 19, 2024, Página(s) e0301969, ISSN 1932-6203
Editor: Public Library of Science
DOI: 10.1371/journal.pone.0301969

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

Autores: Natália Alves, Joeran S. Bosma, Kiran V. Venkadesh, Colin Jacobs, Zaigham Saghir, Maarten de Rooij, John Hermans, Henkjan Huisman
Publicado en: Radiology, Edición 308, 2023, ISSN 0033-8419
Editor: Radiological Society of North America
DOI: 10.1148/radiol.230275

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

Autores: Megan Schuurmans, Natália Alves, Pierpaolo Vendittelli, Henkjan Huisman, John Hermans, PANCAIM Consortium
Publicado en: Gastroenterology, Edición Volume 165, Edición 2, 2023, Página(s) 309-316, ISSN 1528-0012
Editor: American Gastroenterological Association
DOI: 10.1053/j.gastro.2023.04.003

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

Autores: Marianna Vitaloni, Patrick Michl, Matthias Löhr, Ali Stunt, Patrycja Rzadkowska, Eva Backman, Lama Sharara, Vitor Neves, Thomas Gruenberger, Zorana Maravic
Publicado en: Journal of Patient Experience, Edición 9, 2025, ISSN 2374-3735
Editor: SAGE Publications
DOI: 10.1177/23743735221112633

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

Autores: 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
Publicado en: Gut, Edición 74, 2025, Página(s) 2024-2034, ISSN 0017-5749
Editor: BMJ Publishing Group
DOI: 10.1136/gutjnl-2024-334237

The DRAGON benchmark for clinical NLP

Autores: 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
Publicado en: npj Digital Medicine, Edición 8, 2025, ISSN 2398-6352
Editor: 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?

Autores: J.-Matthias Löhr, Daniel Öhlund, Emma Söreskog, Emil Andersson, Miroslav Vujasinovic, Niklas Zethraeus, Malin Sund
Publicado en: Familial Cancer, Edición 23, 2024, Página(s) 399-403, ISSN 1389-9600
Editor: Kluwer Academic Publishers
DOI: 10.1007/s10689-024-00363-6

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

Autores: J-Matthias Löhr, Miroslav Vujasinovic, Nikolaos Kartalis, Philipp Osten
Publicado en: eGastroenterology, Edición 2, 2025, Página(s) e100082, ISSN 2766-0125
Editor: BMJ
DOI: 10.1136/egastro-2024-100082

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

Autores: Alberto López, John Zobolas, Ole Christian Lingjærde, Daniel Nebdal, Thomas Fleischer, Tero Aittokallio
Publicado en: Nordic Machine Intelligence, Edición 4, 2024, Página(s) 26-42, ISSN 2703-9196
Editor: University of Oslo Library
DOI: 10.5617/nmi.10584

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

Autores: Megan Schuurmans, Anindo Saha, Natália Alves, Pierpaolo Vendittelli, Derya Yakar, Sergio Sabroso-Lasa, Nannan Xue, Núria Malats, Henkjan Huisman, John Hermans, Geert Litjens
Publicado en: European Radiology, Edición 35, 2025, Página(s) 7537-7548, ISSN 1432-1084
Editor: 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

Autores: Natália Alves; Megan Schuurmans; Geke Litjens; Joeran S. Bosma; John Hermans; Henkjan J. Huisman
Publicado en: Cancers, Edición 14(2), 376, 2022, ISSN 2072-6694
Editor: 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

Autores: Kieran D. Lamb, Martha M. Luka, Megan Saathoff, Richard J. Orton, My V. T. Phan, Matthew Cotten, Ke Yuan, David L. Robertson
Publicado en: PLOS Computational Biology, Edición 20, 2024, Página(s) e1011795, ISSN 1553-7358
Editor: Public Library of Science (PLoS)
DOI: 10.1371/journal.pcbi.1011795

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

Autores: Megan Schuurmans; Natália Alves; Pierpaolo Vendittelli; Henkjan Huisman; John Hermans
Publicado en: Cancers, Edición 14(14), 3498, 2022, ISSN 2072-6694
Editor: Multidisciplinary Digital Publishing Institute (MDPI)
DOI: 10.3390/cancers14143498

Other (4)

Tutorial on survival modelling with omics data

Autores: Zhi Zhao, John Zobolas, Manuela Zucknick, Tero Aittokallio
Publicado en: 2023
Editor: Arxiv
DOI: 10.48550/arxiv.2302.12542

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

Autores: Zobolas, John; Aittokallio, Tero
Publicado en: Edición 7, 2023
Editor: PANCAIM Consortium
DOI: 10.5281/zenodo.8119247

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

Autores: Pierpaolo Vendittelli, John-Melle Bokhorst, Esther Smeets, Valentyna Kryklyva, Lodewijk Brosens, Caroline Verbeke, Geert Litjens
Publicado en: 2023
Editor: Research Square Platform LLC
DOI: 10.21203/rs.3.rs-3307605/v1

An example Machine Learning Survival Workflow

Autores: Zobolas, John
Publicado en: Edición 1, 2022
Editor: Zenodo
DOI: 10.5281/zenodo.8060668

Conference proceedings (1)

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

Autores: Vendittelli, Pierpaolo; Smeets, Esther M. M.; Litjens, Geert
Publicado en: Proceedings of the SPIE, Volume 12039, 2022
Editor: SPIE
DOI: 10.1117/12.2611542