The convergence of the metaverse, artificial intelligence (AI), and federated learning reshapes the future of healthcare ecosystems by blending immersive digital environments with intelligent, privacy-preserving data systems. As virtual care platforms expand and AI-driven diagnostics become more sophisticated, federated learning enables institutions to train algorithms without sharing sensitive patient data, strengthening innovation and security. Together, these technologies may create patient-centered ecosystems where simulation, predictive analytics, and data governance enhance clinical decision-making and expand access to care. The Convergence of the Metaverse, AI, and Federated Learning in Healthcare Ecosystems explores the transformative convergence of three cutting-edge technological domains in medicine. It examines federated learning as the privacy-preserving machine learning paradigm that unlocks collaborative AI development. This book covers topics such as healthcare diagnostics, medical imaging, and wearable technology, and is a useful resource for business owners, engineers, medical and healthcare professionals, academicians, researchers, and scientists.