Learn about Federated Learning (FL) in healthcare through this 24-minute conference talk from the Toronto Machine Learning Series, presented by John Jewell from Vector Institute's Applied Machine Learning team. Explore how FL enables training machine learning models across distributed healthcare datasets without centralizing sensitive data. Discover the FL4Health library developed at Vector Institute and its practical applications in clinical settings. Examine common challenges in distributed data environments like data drift and heterogeneity, along with modern solutions to address these issues. Gain insights into experimental results demonstrating successful implementation of FL for training high-performing models while maintaining data privacy and regulatory compliance in healthcare applications.