Using Block chain Systems for Encrypting Individual Medical Records

Artificial intelligence (AI) has been utilized in the healthcare sector for decades, supporting a extensive collection of proposals. Through machine learning and AI algorithms, it has become possible to improve diagnostics, initial conduct tactics, and improve enduring results. During the COVID-19 pandemic, AI models were notably employed to predict symptoms, track the virus’s spread, and accelerate research and treatment using medical data. Despite these advancements, deploying AI in real-time, real-world healthcare settings presents significant challenges. One major issue is the reluctance of organizations to share sensitive patient data with third parties due to privacy concerns. Additionally, the fragmented nature of enduring information transversely unlike healthcare schemes makes it difficult to develop a generalized predictive model. To talk these subjects, this paper proposes a solution that integrates block chain and AI technologies. Block chain can ensure secure and controlled access to medical data, while federated learning—a decentralized AI approach—can enable the development of robust, real-time models without compromising data privacy.