European Federation for Cancer Images (EUCAIM)

Purpose and goal: *Maskinöversatt*

The project aims to create a pan-European digital federated infrastructure of FAIR cancer-related de-identified images to provide a platform for the development and benchmarking of AI tools for precision medicine. EUCAIM builds on the EU projects in AI for health imaging (AI4HI), European research infrastructures and databases as well as national or regional repositories of clinical images, pathology, molecular data and laboratory data.

Finally, a validated clinical decision system that supports diagnosis, treatment and predictive medicine must be created Expected results and effects:

Deployment of interoperable, FAIR compliant and secure infrastructure including data governance for cancer data, open to the involvement of new stakeholders.

Tools and services for distributed analysis, AI learning and clinical validation by use of imaging data and related clinical information. New, adapted or extended cancer image data sources (including image annotation). Cancer images of different cancer types useful for developing clinically relevant AI

Linking between the cancer imaging data infrastructure and the Testing and Experimentation Facility (TEF) for Health. Approach and implementation:

WP2 will establish relationships with different health data providers (repositories, hospitals) and ensure data is available. WP3 Ethical and legal aspects will ensure compliance with aspects such as data security and privacy regulations and legislation. WP4 is the central hub.

WP5 will define a common data model, specify requirements and implement tools for data interoperability, and define a framework for nodes. WP6 designs and implements a framework for distributed analysis. WP7 will test, validate, and expand the platform. Business and sustainability is done in WP8.