UNICA is a European research and innovation project dedicated to revolutionising cancer screening through secure, AI-powered data sharing. By connecting hospitals, researchers, and technology providers, UNICA enables the EUCAIM federated network to expand across Europe, unlocking the potential of large-scale cancer imaging data for faster, more accurate, and personalised detection.
UNICA's mission is to transform cancer imaging and early detection by:
- Empowering hospitals to share imaging data securely, enabling cross-border research and collaboration
- Integrating AI-driven tools into clinical workflows, supporting early diagnosis of breast, lung, and prostate cancers
- Ensuring patient empowerment, privacy, and ethical data use through clear governance and opt-in/opt-out procedures
- Strengthening Europe's research capacity and providing a replicable model for other medical domains
Project Objectives
Perform cancer data standardisation by applying FAIR principles in alignment with EUCAIM's standards
Assist hospitals in making patient data FAIR by applying a common schema that enables interoperability and reuse of cancer imaging data for research and AI development. This includes completing data-protection authorizations, implementing data-warehouse guidelines, cataloguing data, and mapping ontologies for EUCAIM integration. Curation will follow EHDS and EEHRxF specifications, with all legal and ethical requirements addressed. Standard procedures for access and reuse will be defined, and pseudonymization applied by default, followed by quality and integrity checks. The goal is to deliver high-quality lung, breast, and prostate cancer datasets for federated analysis.
Expand the geographical coverage of the European Cancer Imaging Infrastructure (EUCAIM) by onboarding new imaging data repositories from underrepresented regions
Medical centres in Greece, Germany, Slovenia, Ukraine, Portugal, Lithuania, and Poland are supported in activating EUCAIM federated nodes and contributing screening-based cancer imaging data. GDPR compliance and all required legal frameworks—such as infrastructure, data-use, and joint-controller agreements—are ensured. The objective is to expand the availability of high-quality lung, breast, and prostate cancer data within EUCAIM for secondary research and innovation.
Demonstrate the adoption and integration of AI-based technologies for cancer imaging analysis by piloting advanced AI models
Non-technical partners will first receive training on distributed datasets and federated learning. Using the EUCAIM infrastructure, the project will then demonstrate AI tools for cancer screening, piloting breast cancer risk assessment and lung cancer detection from X-rays as proofs of concept. Development will follow European trustworthy AI guidelines, with emphasis on explainability. Standard AI performance metrics (e.g., confusion matrices, accuracy) will be used, complemented by indicators such as clinician participation and improvements in diagnostic outcomes with AI support.
Ensure comprehensive alignment with key EU initiatives
To avoid duplication of efforts and maximise impact, the project will maintain close coordination with the EUCAIM initiative throughout its duration. Additionally, it will seek alignment with other relevant EU-funded initiatives, including but not limited to EHDS infrastructures (MyHealth@EU), Europe's Beating Cancer Plan, Cancer Mission, EU4Health funded projects, XtEHR (EEHRxF) and TEHDAS 2 joint actions, QUANTUM, and the HealthData@EU pilot project. Meetings, technical workshops, webinars, and collaborative events and publications will be organised to foster synergies and ensure alignment with these initiatives.
Promote patient empowerment through targeted communication strategies and dissemination
This project promotes patient data altruism by encouraging individuals to donate health data for public-interest research. Trust will be built through clear opt-in/opt-out mechanisms, strong anonymization, and transparent governance. Non-monetary incentives—such as personalised insights and citizen-science involvement—will further motivate participation. Collaboration with data-altruism organisations and advocacy groups will support outreach, complemented by workshops and educational materials on the value and ethics of data reuse. Joint communication activities will share results, best practices, and scientific outputs with the public, academics, clinicians, hospitals, and stakeholders interested in EUCAIM. Capacity-building will address AI-driven health data analysis, federated learning, and the European Health Data Space.