Guest Speaker: Prof. Dr. Shadi Albarqouni (view profile in Research Directory)
Topic: Towards Equitable and Affordable Medicine with Federated Learning — Leveraging Collective Intelligence for Inclusive Global Healthcare
Registration: https://uni-ms.zoom-x.de/meeting/register/u50od-CvrDMuHtXJnlP2uYlKjHV3hkqSD3jR
The Series directs special attention towards the added value of interdisciplinary and international cooperation in global health research. Every first Tuesday of the month, speakers share insights into their research projects while focusing on research processes, methods as well as lessons learned. Following the 30-minute speaker’s presentation, the Series encourages an academic exchange between the speaker and the audience in a 30-minute Q&A session.
In this edition of the GLOHRA Academy Series, Prof. Dr. Shadi Albarqouni will introduce Federated Learning as a secure and efficient way of AI use in healthcare. Deep Learning (DL) stands at the forefront of artificial intelligence, revolutionizing computer science with its prowess in various tasks, especially in computer vision and medical applications. Yet, its success hinges on vast data resources, a challenge exacerbated in healthcare by privacy concerns. Enter Federated Learning, a groundbreaking technology poised to transform how DL models are trained without compromising data security. By allowing local hospitals to share only trained parameters with a centralized DL model, Federated Learning fosters collaboration while preserving privacy. However, hurdles persist, including heterogeneity, domain shift, data scarcity, and multi-modal complexities inherent in medical imaging. In this illuminating talk, we delve into the clinical workflow and confront the common challenges facing AI in Medicine. Our focus then shifts to Federated Learning, exploring its promise, pitfalls, and potential solutions. Drawing from recent breakthroughs, including a compelling MR Brain imaging case study published in Nature Machine Intelligence, we navigate the landscape of secure and efficient AI adoption in healthcare
Prof. Albarqouni is a GLOHRA Steering Committee Member and Professor of Computational Medical Imaging Research at the University of Bonn, and AI Young Investigator Group Leader at Helmholtz AI. With significant roles at Imperial College London, ETH Zurich, and the Technical University of Munich (TUM), his impact reverberates through his 100+ publications in esteemed journals and conferences. His expertise extends beyond academia, with contributions as an Associate Editor at IEEE Transactions on Medical Imaging and evaluator for national and international grants like DFG, BMBF, and EC. Recognized with awards like the DAAD PRIME Fellowship, Prof. Albarqouni fosters collaboration through AGYA and ELLIS memberships and initiatives like the Palestine Young Academy and the RISE-MICCAI community, focusing on innovative medical solutions and knowledge transfer to emerging countries.