The paper explores the integration of Federated Learning (FL) and blockchain in decentralized data-sharing, particularly in the healthcare sector. It highlights the challenges of centralized data-sharing, such as privacy, security, and interoperability issues, and proposes a decentralized approach to address these challenges. The authors argue that FL, a decentralized machine learning paradigm, enables collaborative AI model training without sharing raw patient data, while blockchain provides a transparent and immutable ledger, fostering trust, security, and data integrity. The paper outlines the technical foundations of FL and blockchain, emphasizing their roles in reshaping healthcare data-sharing. It demonstrates the potential impact of this fusion on patient care, preserving privacy while granting access to diverse datasets, leading to more accurate models and improved diagnoses. The findings underscore the potential acceleration of medical research, improved treatment outcomes, and patient empowerment through data ownership. The synergy of FL and blockchain envisions a healthcare ecosystem that prioritizes individual privacy and propels advancements in medical science.The paper explores the integration of Federated Learning (FL) and blockchain in decentralized data-sharing, particularly in the healthcare sector. It highlights the challenges of centralized data-sharing, such as privacy, security, and interoperability issues, and proposes a decentralized approach to address these challenges. The authors argue that FL, a decentralized machine learning paradigm, enables collaborative AI model training without sharing raw patient data, while blockchain provides a transparent and immutable ledger, fostering trust, security, and data integrity. The paper outlines the technical foundations of FL and blockchain, emphasizing their roles in reshaping healthcare data-sharing. It demonstrates the potential impact of this fusion on patient care, preserving privacy while granting access to diverse datasets, leading to more accurate models and improved diagnoses. The findings underscore the potential acceleration of medical research, improved treatment outcomes, and patient empowerment through data ownership. The synergy of FL and blockchain envisions a healthcare ecosystem that prioritizes individual privacy and propels advancements in medical science.