Discover the most recent accomplishments and resources from the ODELIA project as we continue to push the boundaries of cancer diagnostics and treatment.
Dive into our latest scientific publications, where our team of experts share cutting-edge research and findings that are shaping the future of cancer care.
Browse through our comprehensive public deliverables and reports to stay up-to-date with the project’s progress and learn about the milestones we have achieved.
Finally, take advantage of our innovative online tools, developed to provide researchers, clinicians, and innovators with access to invaluable data and insights, ultimately driving transformative advancements in cancer diagnostics and treatment.
| Title | Author(s) | Journal | Date | DOI |
|---|---|---|---|---|
| Denoising diffusion probabilistic models for 3D medical image generation | F. Khader et al. | Nature Scientific Reports | 05.05.23 | 10.1038/s41598-023-34341-2 |
| Large language models streamline automated machine learning for clinical studies | S. T. Arasteh et al. | Nature Communications | 21.02.24 | 10.1038/s41467-024-45879-8 |
| Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging | S. T. Arasteh et al. | Nature Communications Medicine | 14.03.24 | 10.1038/s43856-024-00462-6 |
| Diffusion probabilistic versus generative adversarial models to reduce contrast agent dose in breast MRI | G. Müller-Franzes et al. | European Radiology Experimental | 01.05.24 | 10.1186/s41747-024-00451-3 |
| Large language models could make natural language again the universal interface of healthcare | J. N. Kather et al. | Nature Medicine | 23.08.24 | 10.1038/s41591-024-03199-w |
| Reconstruction of patient-specific confounders in AI-based radiologic image interpretation using generative pretraining | T. Han et al. | Cell Reports Medicine | 17.09.24 | 10.1016/j.xcrm.2024.101713 |
| Prompt injection attacks on vision language models in oncology | J. Clusmann et al. | Nature Communications | 01.02.25 | 10.1038/s41467-024-55631-x |
| Swarm learning with weak supervision enables automatic breast cancer detection in magnetic resonance imaging | O. L. Saldanha et al. | Nature Communications Medicine | 06.02.25 | 10.1038/s43856-024-00722-5 |
| Medical slice transformer for improved diagnosis and explainability on 3D medical images with DINOv2 | G. Müller-Franzes et al. | Nature Scientific Reports | 04.07.25 | 10.1038/s41598-025-09041-8 |
| Overcoming regulatory barriers to the implementation of AI agents in healthcare | O. Freyer et al. | Nature Medicine | 18.07.25 | 10.1038/s41591-025-03841-1 |
| meval: A Statistical Toolbox for Fine-Grained Model Performance Analysis | D. Sutariya et al. | arXiv | 19.12.25 | 10.1007/978-3-032-05870-6_19 |
| A European Multi-Center Breast Cancer MRI Dataset | G. Müller-Franzes et al. | arXiv | 24.12.25 | 10.48550/arXiv.2506.00474 |
| Title | Author(s) | Date | Access |
|---|---|---|---|
| D7.3 Project Video | EIBIR | 22/12/2023 | DOWNLOAD |
| D2.7 Midterm recruitment report | CAM | 22/12/2023 | DOWNLOAD |
| D1.4 Instructions on training AI models with SL in a tangible demonstration | TUD | 11/12/2023 | DOWNLOAD |
| D1.3 Manual on setting up SL onsite | TUD | 21/9/2023 | DOWNLOAD |
| D1.2 Guidance document on running SL in clinical environments | TUD | 21/9/2023 | DOWNLOAD |
| D7.1 Communication kit including website | EIBIR | 28/4/2023 | DOWNLOAD |
| D1.1 Setting up SL capable compute infrastructure | TUD | 28/4/2023 | DOWNLOAD |
| D2.6 Study Initiation Package | UKA | 31/1/2023 | DOWNLOAD |
| D2.1 Report comparing the performance of locally trained models against swarm-trained models in breast cancer screening | CAM | 19/12/2024 | DOWNLOAD |
| D2.2 Trained neural networks for detection of breast cancer in MRI images (including models trained on local data only and models trained in the swarm) | UKA | 19/12/2024 | DOWNLOAD |
| D2.3 Public MRI dataset including 500 examinations | CAM | 30/6/2025 | DOWNLOAD |
| D4.1 Web front-end | SAI | 30/6/2025 | DOWNLOAD |
| D4.2 Source code for the web front-end | SAI | 30/6/2025 | DOWNLOAD |
| D4.3 Updated web front-end | SAI | 22/12/2025 | DOWNLOAD |
| D7.7 Report on summer schools | EIBIR | 22/12/2025 | DOWNLOAD |
| Name | Descriptions | Date | Access |
|---|---|---|---|
| Swarm Learning Documentation Website | Technical instructions how to set up and reuse the Odelia technical platform for other use cases | 20/10/2023 | odelia-ai.github.io |
| ODELIA Flyer | Flyer about the ODELIA project | 21/2/2023 | DOWNLOAD |
| Press Release | Press release announcing the start of the ODELIA project | 3/2/2023 | DOWNLOAD |
| ODELIA Logo | Project logo | 31/1/2023 | DOWNLOAD |
