The integration of artificial intelligence (AI) into medical cyber-physical systems has led to novel approaches for managing healthcare data. However, centralizing healthcare data poses risks to privacy and security. Decentralized approaches offer a promising solution to balance the need for information sharing with individual privacy protection. This chapter explores the Solid platform for decentralized healthcare data management, such as electronic health records (EHR) and Federated Learning (FL) that emerges as a technique to extract knowledge from distributed data while preserving user privacy. Despite the benefits, challenges remain in adopting decentralized approaches, including the need for standards, patient and healthcare professional education, and ethical considerations. Moreover, patients play a crucial role in decentralized healthcare data management, necessitating informed involvement in data control decisions. Nonetheless, FL holds promise for personalized medicine, advancing healthcare delivery, enhancing patient outcomes, accelerate medical research and addressing regulatory compliance challenges in the medical field.