Join EASAC and FEAM for the launch of our joint report on artificial intelligence (AI) in European healthcare. The event will feature two panel discussions with policymakers, regulators, healthcare professionals and patient representatives on what it takes to bring AI into medicine safely and effectively.
* Seats are limited for in-person attendance, and early registration is encouraged to secure a place. A sandwich lunch will be provided for in-person attendees at the hall from 12:30 CEST. For online participation, please register in advance to receive the livestream link.
Since 2024
EASAC and the Federation of European Academies of Medicine (FEAM), with their respective member academies, have been collaborating since 2024 to explore how AI-powered health products and services can be effectively evaluated and safely integrated into European healthcare. Their joint report, AI in European Healthcare: Policy Recommendations for Optimising Added Value and Safe, Ethical, and Inclusive Adoption, will be launched on 30 September 2026, from 13:00 to 15:00 CEST at Arts 56 (Avenue des Arts 56, 1000 Brussels), with live streaming available.
This EASAC-FEAM report has been written by a working group of 22 members from across Europe, co-chaired by André Knottnerus (EASAC) and Luis Martí-Bonmatí (FEAM). It examines evidence generation, including randomised and pragmatic trial designs, as well as the regulatory framework governing AI, addressing key legislation such as the Medical Device Regulation, the AI Act, the European Health Data Space, and the Product Liability Directive.
Alongside regulatory considerations, the working group has analysed data interoperability across health systems, the ethical dimensions of AI in healthcare, privacy, transparency, model explainability, equitable access, and the workforce and education changes required to effectively implement these tools.
Read more about the EASAC–FEAM project on feam.eu →
View the project on easac.eu →
30 Sept
How Europe ensures AI in healthcare delivers added-value and is safe before it reaches patients, and who is accountable when it isn’t.
What it takes to deploy AI safely in a hospital and what it takes for patients to trust it once it’s there.
