In my presentation I will explore the critical role of AI in transforming the landscape of health data management across Europe. Drawing from my extensive experience as a researcher in AI and FAIR data infrastructures, as well as my involvement in various international research projects, I will present how AI-driven solutions can revolutionize the curation, integration, and reuse of personal health data. This presentation will highlight the challenges of fragmented health data, the potential of AI to automate data curation processes, and the importance of creating interoperable and patient-centric health records. By showcasing real-world examples and use cases, I aim to demonstrate how these advancements can empower patients and enhance clinical research.

More and more, people start to appreciate the importance and value of data. This is not only accelerated by the ongoing growth and adoption of AI, but also because it is one of the cornerstones of the EU data-strategy. More specifically, the EU data-strategy also encourages to increase the potential of data by supporting data sharing approaches using ‘data spaces’. In his talk Hans will high-light what data spaces are and how they relate to working with health-related data in the EU. He will use a number of examples from his own experience to describe the current state-of-practice and identify challenges and opportunities going forward.

The purpose of the presentation will be to give an overview of the regulatory requirements and challenges which apply to manufacturers of AI-based medical devices in the EU. The presentation will start with a discussion of current key considerations for the CE marking of these devices under the EU MDR and IVDR before analysing the impact and challenges posed by the AI Act on future conformity assessments; The presentation will also include some considerations from a healthcare professional perspective on the use of AI-based medical devices in daily practices.

• The EU and US AI Act
• Differences in their implementation for AI in healthcare
• Potential pathways to measure medical and economic impact of AI in healthcare
• Ethical Guidelines in AI-driven healthcare decision-making

Developing AI systems for use in medical settings is a complex, multi-stage process. Relatively few AI developers publish the methodology of such developments. While healthcare organisations and physicians see many approved devices without sufficient evidence, startups and companies developing AI systems are demanding technical, operational and ethical standards. Meanwhile, regulators such as the US Food and Drug Administration (FDA) or the European Medicines Agency (EMA) have approved hundreds of AI-powered systems for use in hospitals and clinics through less rigorous processes than those for drugs.

It has become clear to policymakers, regulators, clinicians, patients and the scientific and technological community that AI standardisation should be implemented to ensure patient rights, fundamental values and the desired impact on healthcare organisations. The presentation aims to share the CHAIMELEON’s findings in this specific topic. A preliminary toolkit with guidelines related to the design, development and validation of AI systems in healthcare will be shared with the audience. Finally, some concrete examples of AI models in the health domain will be presented.