Discover unique insights and approaches to imaging informatics from our European colleagues. This session will highlight transformative practices and collaborative efforts shaping the future of healthcare innovation across the region. 

Join us to explore key topics in AI for medical imaging, beginning with federated learning, which enables training deep learning models across multiple locations without transferring imaging data. It then examines radiologist-machine interaction, addressing automation bias, deskilling, education, and interface design, and how these factors impact user experience, performance, and clinical decision-making. Finally, it covers early health technology assessment in AI, emphasizing the need for transparent value evaluations during development to drive meaningful adoption in clinical practice. 

This session is presented in collaboration with the the European Society of Medical Imaging Informatics (EuSoMII)

Objectives

• Describe innovative imaging informatics practices implemented by European healthcare organizations. 
• Identify collaborative strategies used to address challenges in imaging informatics across diverse healthcare systems. 
• Compare key differences in imaging informatics approaches between European and global contexts. 
• Understand different paradigms to study human-AI interaction and identify appropriate evaluation methods. 
• Know about the different options of how AI results may be returned in the workflow and understand the implications of the choice of integration.