Explore the transformative potential of federated learning in global health. Federated learning enables the development of robust AI models by allowing collaboration across multiple institutions without sharing sensitive patient data, addressing critical privacy concerns. This talk will highlight real-world applications where federated learning has improved healthcare outcomes, particularly in low-resource settings. By enabling secure, decentralized data analysis, this technology fosters global cooperation in disease detection, diagnosis, and treatment, offering a path forward for AI-driven healthcare advancements on a global scale.