December 19, 2023

Federated Learning and Analysis for Collaborative Research in Healthcare at a National and International Scale

The first joint publication from Regional Leaders Summit (RLS)-Digital Health—Federated Learning and Analysis for Collaborative Research in Healthcare at a National and International Scale—was launched on December 14 with financial support from the Fonds de recherche du Québec- Nature et technologies and the Consortium Santé Numérique Université de Montréal. This white paper is a reflection of current literature, expert interviews with researchers and practitioners in the RLS partner regions (Bavaria, Georgia, Québec, São Paulo, Shandong, and Upper Austria) and case studies of existing projects.

  • Download the English version here
  • Down the French version here

The present White Paper chooses to approach the advancement of Big Data and AI in healthcare by focusing on a major trend in digital health: Federated Learning (FL) and Federated Analysis (FA). This approach proposes to harness the full potential of health data by enabling the secure exploitation of multiple data sources without having to pool data in a single site (AbdulRhaman, 2020). FL/FA can be presented as a response to present legal, ethical, and technical challenges that limit data sharing across institutions and jurisdictions and thereby reduce the capacity to conduct collaborative data-driven research at a national and international scale (Kairouz et al., 2021).

While FL/FA presents genuine opportunities for the enhancement of Big Data and AI for research and innovation, this approach also raises several questions regarding privacy protection, data reliability, and resource utilization, among others. These are the specific issues investigated in this document. While exploring the potential and challenges of FL/FA for collaborative research in digital health, this white paper also describes robust platforms and technologies showing how FL/FA can be made possible in today’s healthcare systems.