A survey on intelligent secure and distributed frameworks for Healthcare 5.0

Healthcare 5.0 represents the next significant evolution in healthcare, emphasizing the integration of cutting-edge technologies such as the Internet of Medical Things, Artificial Intelligence, and Blockchain to offer more personalized, efficient, and secure medical services. Unlike its predecessors, Healthcare 5.0 focuses on enhancing human capabilities through technology rather than replacing human roles, aiming for a collaborative environment between patients, healthcare providers, and advanced systems. This review explores the historical development of healthcare systems from basic human-driven care to the automated and digitalized Healthcare 4.0, ultimately leading to the human-centric vision of Healthcare 5.0. This paper provides a comprehensive review of machine learning techniques in improving disease detection and diagnosis. Moreover, a detailed review of the advanced technologies used for predictive care and real-time health monitoring is presented. This article also provides an inclusive review of Federated Learning and Blockchain-based privacy preservation and security techniques used to secure personal healthcare data in the Healthcare 5.0 paradigm. Practical examples such as AI-assisted chronic heart disease prediction, blockchain-enabled secure electronic health records, and federated learning models for COVID-19 diagnosis across multiple hospitals are highlighted to demonstrate real-world impact. Key issues like real-time monitoring, system interoperability, and model transparency are critically assessed, with a focus on current technological solutions such as explainable AI, fog computing, and cloud computing. The paper concludes with a discussion of challenges and future research directions, focusing on further integrating innovative technologies in healthcare while addressing the challenges of data security and system integration, ultimately paving the way for more efficient, secure, and patient-centered care.