This work package ensures the effective coordination of the consortium and the smooth implementation of activities. It oversees administrative, financial, and quality management processes, while also safeguarding compliance with ethical standards and data protection requirements.
This package builds the knowledge base of the project by examining how gender and racial bias appear in biomedical AI. Through reviews of scientific evidence, consultations with experts, and case studies in hospitals, it will identify the ways in which AI systems affect the diagnosis of cardiovascular disease, depression, and diabetes. The findings will be consolidated into a public database and a Biases Report, while also informing a regulatory model designed to promote fairer and more transparent healthcare technologies.
This package transforms project insights into guidance for the future. Drawing on the evidence and lessons collected in earlier phases, it produces recommendations aimed at regulators and policymakers at both national and EU level. Roundtables, policy dialogues, and reports will help decision-makers better understand the risks of bias in biomedical AI and the measures needed to safeguard fundamental rights in the digital transformation of healthcare.

