Sensitive Healthcare Data Analysis Empowered by Federated Learning
Nov 21, 2024 — 03:55 pm CET - 4:15 PM CET
Presented by
Description
This talk will illustrate current advances in federated learning (FL) for sensitive applications in healthcare. In spite of the wide interest in the federated learning paradigm, current applications to sensitive domains, such as healthcare, are still challenging due to the complexity in dealing with heterogeneous and complex data, as well as to the practical difficulty of deploying federated architectures in the real world. The talk will introduce Fed-BioMed, a development initiative aiming at translating federated learning to healthcare applications. Fed-BioMed tackles the challenges required to meet real-world translation, concerning FL security, scalability and interoperability. In addition to this masterclass, a demo on Fed-BioMed will be offered at Inria booth.
