ArticleFrontiers in oncology2022
CHAIMELEON Project: Creation of a Pan-European Repository of Health Imaging Data for the Development of AI-Powered Cancer Management Tools.
Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
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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
23 citing papers in PubMed.
- 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
- From theory to practice: Re-identification Challenge to test imaging data pseudonymization effectiveness.Scientific data · 2026Article
- A framework for a national cancer imaging repository in Nigeria.Scientific reports · 2026Article
- Establishing a Cervical Cytology Biorepository: A Protocol for Advancing Translational Cervical Cancer Research through Biobanking.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
- Ginger Bioactives as Multi-Target Therapeutics: Mechanisms, Delivery Innovation, and Human Health Impact.Nutrients · 2026Review
- Building trust and privacy in cross-border health data sharing for European cancer research.Radiology advances · 2026Review
- Transforming a clinical study database into a structured database adapted to artificial intelligence applications.Insights into imaging · 2026Article
- Predetermined Change Control Plans: Guiding Principles for Advancing Safe, Effective, and High-Quality AI-ML Technologies.JMIR AI · 2025Article
- Application of artificial intelligence in medical imaging for tumor diagnosis and treatment: a comprehensive approach.Discover oncology · 2025Review
- Advancing deep learning-based segmentation for multiple lung cancer lesions in real-world multicenter CT scans.European radiology experimental · 2025Article
- Convergent Mechanisms in Virus-Induced Cancers: A Perspective on Classical Viruses, SARS-CoV-2, and AI-Driven Solutions.Infectious disease reports · 2025Article
- Advancing Medical Imaging Research Through Standardization: The Path to Rapid Development, Rigorous Validation, and Robust Reproducibility.Investigative radiology · 2025Review
- Recommendations for the creation of benchmark datasets for reproducible artificial intelligence in radiology.Insights into imaging · 2024Article
- Review
- Documenting the de-identification process of clinical and imaging data for AI for health imaging projects.Insights into imaging · 2024Article
- The SINFONIA project repository for AI-based algorithms and health data.Frontiers in public health · 2024Article
- Clinical applications of artificial intelligence in radiology.The British journal of radiology · 2023Review
- Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects.European radiology experimental · 2023Review
- Exploring Stakeholder Requirements to Enable Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Results of a Multistep Mixed Methods Study.JMIR formative research · 2023Article
- Interoperable slide microscopy viewer and annotation tool for imaging data science and computational pathology.Nature communications · 2023Article
Corrections and comments
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Authors and funding
21 authors.
Funding
Abstract
The CHAIMELEON project aims to set up a pan-European repository of health imaging data, tools and methodologies, with the ambition to set a standard and provide resources for future AI experimentation for cancer management. The project is a 4 year long, EU-funded project tackling some of the most ambitious research in the fields of biomedical imaging, artificial intelligence and cancer treatment, addressing the four types of cancer that currently have the highest prevalence worldwide: lung, breast, prostate and colorectal. To allow this, clinical partners and external collaborators will populate the repository with multimodality (MR, CT, PET/CT) imaging and related clinical data. Subsequently, AI developers will enable a multimodal analytical data engine facilitating the interpretation, extraction and exploitation of the information stored at the repository. The development and implementation of AI-powered pipelines will enable advancement towards automating data deidentification, curation, annotation, integrity securing and image harmonization. By the end of the project, the usability and performance of the repository as a tool fostering AI experimentation will be technically validated, including a validation subphase by world-class European AI developers, participating in Open Challenges to the AI Community. Upon successful validation of the repository, a set of selected AI tools will undergo early
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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.