Federated Learning and Artificial Intelligence are the most captivating areas of interest in the healthcare sector and are the most gravitating techniques in intelligent healthcare. Generally, the traditional healthcare system utilizes a centralized party to share the crude data. Therefore, it is prone to several amenities and challenges. However, by agglomerating healthcare with artificial intelligence, the system would afford to communicate effectively between multiple agents and their preferred host. Federated Learning is an exciting feature that works in a decentralized fashion. It maintains communication among user nodes in the preferred system without transferring the raw data. Integrating Federated Learning and Artificial Intelligence techniques in the healthcare system can mitigate several limitations and confrontations. This chapter presents an analytical view of Federated Learning using Artificial Intelligence for applications in the intelligent healthcare sector. Extant vital techniques such as Federated Learning, Artificial Intelligence, and healthcare are discussed. Further unification of Healthcare with Federated Learning-Artificial Intelligence technologies in different spheres is presented. In this chapter, the problems such as privacy, reliability, and stability occurring in the healthcare system are addressed. In addition, the chapter is extended by introducing the solutions of healthcare strategies using Federated Learning and Artificial Intelligence. Finally, the chapter addresses potential research prospects regarding Federated Learning-based Artificial Intelligence in the healthcare management system.