ArticleInsights into imaging2025
Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure.
Article in Insights into imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Deep Learning for Automated Detection and Segmentation of Meningioma on Multiparametric MRI.Journal of imaging informatics in medicine · 2026Article
- Integrating Heterogeneous Real-World Cancer Data for Semantic Interoperability in Oncology and Medical Imaging: Development and Validation of the Cancer Image Europe Hyperontology.Journal of medical Internet research · 2026Article
- Surgery 4.0: From the Smart Operating Room to the Learning Operating Room.Journal of clinical medicine · 2026Article
- Application of artificial intelligence in paediatric oncology imaging.Pediatric radiology · 2026Review
- Potential and challenges of Positron Emission Tomography beyond conventional preclinical and clinical imaging.Zeitschrift fur medizinische Physik · 2026Review
- Bridging the AI chasm in oncology: a standardized platform to enable the in silico clinical validation of AI models within the CHAIMELEON Project.European radiology experimental · 2026Article
- Explainable AI in Cancer Imaging: Scoping Review of Methods, Modalities, and Clinical Integration.Journal of medical Internet research · 2026Article
- Challenges underlying radiology's research problem.Insights into imaging · 2026Review
- Prompting large language models and evaluating inter- and intra-rater agreement for cancer progression assessment from radiology reports.ESMO real world data and digital oncology · 2026Article
- Transforming a clinical study database into a structured database adapted to artificial intelligence applications.Insights into imaging · 2026Article
- APOLLO11: a bio-data-driven model for clinical and translational research in lung cancer.NPJ precision oncology · 2026Article
- The European Health Data Space and biobanking in Europe: synergies, tensions and the future governance of data-driven health research.Frontiers in genetics · 2026Review
- Explainable Radiomics-Based Model for Automatic Image Quality Assessment in Breast Cancer DCE MRI Data.Journal of imaging · 2025Article
- Empowering imaging research through the EUCAIM repository: a new opportunity for ESR journals' authors.European radiology · 2025Article
- Predetermined Change Control Plans: Guiding Principles for Advancing Safe, Effective, and High-Quality AI-ML Technologies.JMIR AI · 2025Article
- How the First Medical Imaging Cancer Atlas EUCAIM Was Populated: The Experience of a Reference Hospital.Open research Europe · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
19 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) is a powerful technology with the potential to disrupt cancer detection, diagnosis and treatment. However, the development of new AI algorithms requires access to large and complex real-world datasets. Although such datasets are constantly being generated, access to them is limited by data fragmentation across numerous repositories and sites, heterogeneity, lack of annotations, and potential privacy issues. The European Cancer Imaging Initiative is a flagship of Europe's Beating Cancer Plan, aiming to unlock the power of AI for cancer patients, clinicians, and researchers by establishing a federated European infrastructure for cancer images through the EU-funded EUropean Federation for CAncer IMages (EUCAIM) project. This infrastructure, called Cancer Image Europe, builds on the AI for Health Imaging network (AI4HI), established European Research Infrastructures (Euro-BioImaging, BBMRI-ERIC, EATRIS, ECRIN, and ELIXIR), and numerous related partners providing access to research tools, images, and related clinical, pathology and molecular data. The infrastructure targets clinicians, researchers, and innovators by providing the means to develop and validate data-intensive AI-based and other IT-enabled clinical decision-making systems supporting precision medicine. Common data models, including a linking hyperontology, quality standards, compliance with the FAIR (Findability, Accessibility, Interoperability and Reusability) principles, data annotation, curation and anonymization services are provided to ensure data quality and interoperability, consistency and privacy. In summer 2024, the EUCAIM project released the first prototype of an EU-wide infrastructure, with a comprehensive dashboard integrating applications for dataset discovery, federated search, data access request, metadata harvesting, annotation, secure processing environments and federated processing. CRITICAL RELEVANCE STATEMENT: EUCAIM's federated infrastructure for cancer image data advances medical research and related AI development in Europe. It addresses the current fragmentation and heterogeneity of data repositories is legally compliant, and facilitates collaboration among clinicians, researchers, and innovators. KEY POINTS: AI solutions to advance cancer care rely on large, high-quality real-world datasets. EUCAIM's federated infrastructure for cancer image data empowers cancer research in Europe. It provides access to research tools, images, and related clinical, pathology and molecular data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.