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ODELIA

Open Consortium for Decentralized Medical Artificial Intelligence

Grant period2023-01-01 - 2027-12-31
Funding bodyEuropean Union
Call numberHORIZON-HLTH-2021-CARE-05
Grant number101057091
IdentifierG:(EU-Grant)101057091

Note: ArtifArtificial Intelligence (AI) will revolutionize healthcare as its diagnostic performance approaches that of clinical experts. In particular, in cancer screening, AI helps patients to make better-informed decisions and reduce medical error. However, this requires large datasets whose collection faces severe practical, ethical and legal obstacles. These obstacles can be overcome with swarm learning (SL) where partners jointly train AI models without sharing any data. Yet, access to SL technology is seriously limited because no studies have implemented SL in a true multinational setup, no practically usable implementation of SL is available, researchers & healthcare providers have no experience with setting up SL networks and policymakers are currently unaware of the broader implications of SL. ODELIA will address & solve these issues: ODELIA will build the first open-source software framework for SL, providing an assembly line for the streamlined development of AI solutions. To serve as a blueprint for future SL-based AI systems, ODELIA partners collaborate as a swarm to develop the first clinically useful AI algorithm for the detection of breast cancer in magnetic resonance imaging (MRI). The size of ODELIA's distributed database will exceed all previous studies and ODELIA's AI models will reach expert-level performance for breast cancer screening. Thereby, ODELIA will not only deliver a useful medical application, but prove the clinical benefit of SL in terms of accelerated development, increased performance and robust generalizability to ultimately save thousands of lives of European patients. ODELIA's success will push partners to serve as nuclei for the exponential growth of the SL network and extend SL to a multitude of medical applications. Thus, patients, healthcare providers and citizens in Europe will be provided with a digital infrastructure that enables development of expert-level AI tools on big data without compromising data safety and data privacy.
   

Recent Publications

All known publications ...
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Visual Large Language Models in Radiology: A Systematic Multimodel Evaluation of Diagnostic Accuracy and Hallucinations
Life : open access journal 16(1), 66 () [10.3390/life16010066] special issue: "Current and Future Perspectives of Artificial Intelligence in Medicine / Special Issue Editors: Dr. Giuseppe Consorti, Guest Editor; Dr. Lisa Catarzi, Guest Editor; Dr. Guido Gabriele, Guest Editor"  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;
Reply to the Letter to the Editor: GPT-4o in radiology—a review of label extraction accuracy and clinical applications in upper extremity imaging
European radiology 36(4), 2660-2661 () [10.1007/s00330-026-12350-9]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;
Large language model-based uncertainty-adjusted label extraction for artificial intelligence model development in upper extremity radiography
European radiology 36(4), 2646-2657 () [10.1007/s00330-025-12102-1]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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The Impact of Access to Clinical Guidelines on LLM-Based Treatment Recommendations for Chronic Hepatitis B
Liver international 45(10), e70324 () [10.1111/liv.70324]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Deep Learning Reveals Liver MRI Features Associated With PNPLA3 I148M in Steatotic Liver Disease
Liver international 45(7), e70164 () [10.1111/liv.70164]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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AI in motion: the impact of data augmentation strategies on mitigating MRI motion artifacts
European radiology 35(11), 6865-6878 () [10.1007/s00330-025-11670-6]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;  ;
Revolution or risk?—Assessing the potential and challenges of GPT-4V in radiologic image interpretation
European radiology 35(3), 1111-1121 () [10.1007/s00330-024-11115-6]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Diffusion probabilistic versus generative adversarial models to reduce contrast agent dose in breast MRI
European radiology experimental 8(1), 53 () [10.1186/s41747-024-00451-3]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Time-efficient combined morphologic and quantitative joint MRI: an in situ study of standardized knee cartilage defects in human cadaveric specimens
European radiology experimental 8(1), 66 () [10.1186/s41747-024-00462-0]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Journal Article  ;  ;  ;  ;  ;  ;  ;
The Treasure Trove Hidden in Plain Sight: The Utility of GPT-4 in Chest Radiograph Evaluation
Radiology 313(2), e233441 () [10.1148/radiol.233441]  GO BibTeX | EndNote: XML, Text | RIS

All known publications ...
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 Record created 2023-02-24, last modified 2023-02-25



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