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CORDIS - Resultados de investigaciones de la UE
CORDIS

Open Consortium for Decentralized Medical Artificial Intelligence

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

Source code for the web front-end (se abrirá en una nueva ventana)

The complete source code for the web front-end, shared publicly and open access

Project Video (se abrirá en una nueva ventana)

First short video/animation to raise awareness of the ODELIA project

Updated web front-end (se abrirá en una nueva ventana)

Updated web front-end (version 2.0) connected to a back-end AI-processing pipeline (can display the results of all ODELIA AI models or uploaded models on a fixed set of data or data uploaded by the user)

Web front-end (se abrirá en una nueva ventana)

A web front-end with basic functionalities (version 1.0, can display the saved results of an AI model for a fixed set of data) will be operational and publicly usable by any stakeholder, including citizen scientists

Manual on setting up SL onsite (se abrirá en una nueva ventana)

Manual describing how to set up SL onsite

Trained neural networks for detection of breast cancer in MRI images (including models trained on local data only and models trained in the swarm) (se abrirá en una nueva ventana)

Trained neural networks for detection of breast cancer in MRI images. This includes trained neural network models trained on local data only and models trained in the swarm.

Report comparing the performance of baseline AI model against the winners of the competition, trained locally and in SL (se abrirá en una nueva ventana)

Report comparing the performance of baseline AI model against the winners of the competition. This included neural networks trained locally and in SL.

Communication kit including website (se abrirá en una nueva ventana)

Communication kit for ODELIA, including communication, dissemination and design assets such as a presentation template, standard slides introducing the project, a short project description, the logo and related visual assets, and the project website and online presence.

Report on summer schools (se abrirá en una nueva ventana)

Report summarising the different summer schools organised by ODELIA

Midterm recruitment report (se abrirá en una nueva ventana)

This report is due when 50% of the study population is recruited. The report includes an overview of the number of recruited participants by clinical sites, any problems in recruitment and, if applicable, a detailed description of implemented and planned measures to compensate for any incurred delays.

Guidance document on running SL in clinical environments (se abrirá en una nueva ventana)

Guidance document for partners describing how to run SL in clinical environments

Instructions on training AI models with SL in a tangible demonstration case (se abrirá en una nueva ventana)

Report with instructions on how to train AI models with SL based on a tangible demonstration case

Report comparing the performance of locally trained models against swarm-trained models in breast cancer screening (se abrirá en una nueva ventana)
Study initiation package (se abrirá en una nueva ventana)

Study initiation package (before enrolment of the first study participant)This deliverables includes:- Registration number of the clinical study in a registry meeting WHO Registry criteria- Final version of study protocol as approved by the regulator(s) / ethics committee(s)- Regulatory and ethics approvals required for the enrolment of the first study participant

Publicaciones

meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis (se abrirá en una nueva ventana)

Autores: Dishantkumar Sutariya, Eike Petersen
Publicado en: Lecture Notes in Computer Science, Fairness of AI in Medical Imaging, 2025
Editor: Springer Nature Switzerland
DOI: 10.1007/978-3-032-05870-6_19

Swarm learning with weak supervision enables automatic breast cancer detection in magnetic resonance imaging (se abrirá en una nueva ventana)

Autores: Oliver Lester Saldanha; Jiefu Zhu; Gustav Müller-Franzes; Zunamys I. Carrero; Nicholas R. Payne; Lorena Escudero Sánchez; Paul Christophe Varoutas; Sreenath Kyathanahally; Narmin Ghaffari Laleh; Kevin Pfeiffer; Marta Ligero; Jakob Behner; Kamarul A. Abdullah; Georgios Apostolakos; Chrysafoula Kolofousi; Antri Kleanthous; Michail Kalogeropoulos; Cristina Rossi; Sylwia Nowakowska; Alexandra Athanasiou; Raquel Perez-Lopez; Ritse Mann; Wouter Veldhuis; Julia Camps; Volkmar Schulz; Markus Wenzel; Sergey Morozov; Alexander Ciritsis; Christiane Kuhl; Fiona J. Gilbert; Daniel Truhn; Jakob Nikolas Kather
Publicado en: Communications Medicine, Edición 5, 38 (2025), 2025, ISSN 2730-664X
Editor: Springer Nature
DOI: 10.18154/RWTH-2025-10188

Large language models could make natural language again the universal interface of healthcare (se abrirá en una nueva ventana)

Autores: Jakob Nikolas Kather; Dyke Ferber; Isabella C. Wiest; Stephen Gilbert; Daniel Truhn
Publicado en: Nature Medicine, 2024, ISSN 1546-170X
Editor: Springer Nature
DOI: 10.1038/S41591-024-03199-W

Overcoming regulatory barriers to the implementation of AI agents in healthcare (se abrirá en una nueva ventana)

Autores: Oscar Freyer; Sanddhya Jayabalan; Jakob N. Kather; Stephen Gilbert
Publicado en: Nature Medicine, 2025, ISSN 1546-170X
Editor: Springer Nature
DOI: 10.1038/S41591-025-03841-1

Scientific Reports (se abrirá en una nueva ventana)

Autores: Müller-Franzes, Gustav; Khader, Firas; Siepmann, Robert; Han, Tianyu; Kather, Jakob Nikolas; Nebelung, Sven; Truhn, Daniel
Publicado en: Scientific Reports, Edición (2025) 15:23979, 2025, ISSN 2045-2322
Editor: Springer Nature
DOI: 10.18154/RWTH-2025-06979

Reconstruction of patient-specific confounders in AI-based radiologic image interpretation using generative pretraining (se abrirá en una nueva ventana)

Autores: Tianyu Han; Laura Zigutyte; Luisa Huck; Marc Huppertz; Robert Siepmann; Yossi Gandelsman; Christian Blüthgen; Firas Khader; Christiane Kuhl; Sven Nebelung; Jakob Nikolas Kather; Daniel Truhn
Publicado en: Cell Reports Medicine, 2024, ISSN 2666-3791
Editor: Cell Press (an imprint of Elsevier)
DOI: 10.48550/ARXIV.2309.17123

Nature Communications (se abrirá en una nueva ventana)

Autores: Soroosh Tayebi Arasteh; Tianyu Han; Mahshad Lotfinia; Christiane Kuhl; Jakob Nikolas Kather; Daniel Truhn; Sven Nebelung
Publicado en: Nature Communications, Vol 15, Iss 1, Pp 1-12 (2024), 2024, ISSN 2041-1723
Editor: Nature Publishing Group
DOI: 10.48550/arxiv.2308.14120

Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging (se abrirá en una nueva ventana)

Autores: Soroosh Tayebi Arasteh; Alexander Ziller; Christiane Kuhl; Marcus Makowski; Sven Nebelung; Rickmer Braren; Daniel Rueckert; Daniel Truhn; Georgios Kaissis
Publicado en: Communications Medicine, 2024, ISSN 2730-664X
Editor: Springer Nature
DOI: 10.1038/S43856-024-00462-6

Scientific Reports (se abrirá en una nueva ventana)

Autores: Firas Khader; Gustav Müller-Franzes; Soroosh Tayebi Arasteh; Tianyu Han; Christoph Haarburger; Maximilian Schulze-Hagen; Philipp Schad; Sandy Engelhardt; Bettina Baeßler; Sebastian Foersch; Johannes Stegmaier; Christiane Kuhl; Sven Nebelung; Jakob Nikolas Kather; Daniel Truhn
Publicado en: Scientific Reports, Vol 13, Iss 1, Pp 1-12 (2023), 2023, ISSN 2045-2322
Editor: Nature Publishing Group
DOI: 10.18154/rwth-2023-05893

Diffusion probabilistic versus generative adversarial models to reduce contrast agent dose in breast MRI (se abrirá en una nueva ventana)

Autores: Gustav Müller-Franzes; Luisa Huck; Maike Bode; Sven Nebelung; Christiane Kuhl; Daniel Truhn; Teresa Lemainque
Publicado en: European Radiology Experimental, 2024, ISSN 2509-9280
Editor: SpringerOpen
DOI: 10.1186/S41747-024-00451-3

Nature Communications (se abrirá en una nueva ventana)

Autores: Jan Clusmann; Dyke Ferber; Isabella C. Wiest; Carolin V. Schneider; Titus J. Brinker; Sebastian Foersch; Daniel Truhn; Jakob Nikolas Kather
Publicado en: Nature Communications, 2025, ISSN 2041-1723
Editor: Springer Nature
DOI: 10.1038/S41467-024-55631-X

A European Multi-Center Breast Cancer MRI Dataset

Autores: Gustav Müller-Franzes, Lorena Escudero Sánchez, Nicholas Payne, Alexandra Athanasiou, Michael Kalogeropoulos, Aitor Lopez, Alfredo Miguel Soro Busto, Julia Camps Herrero, Nika Rasoolzadeh, Tianyu Zhang, Ritse Mann, Debora Jutz, Maike Bode, et al
Publicado en: arXiv, Edición 2506.00474, ISSN 2331-8422
Editor: Cornell University

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