Due to the greatly improved capabilities of devices, massive data, and increasing concern
about data privacy, Federated Learning (FL) has been increasingly considered for …

Over the past five years, interest in the literature regarding the security of the Internet of
Medical Things (IoMT) has increased. Due to the enhanced interconnectedness of IoMT …

Abstract Internet of Medical Things (IoMT) has emerged as a combination of sensors,
healthcare devices, and Internet of Things (IoT) to deliver better and intelligent healthcare …

Security in the Metaverse is a critical concern as virtual worlds continue to expand and
evolve. With an increasing number of users engaging in immersive experiences …

As data sharing on the Internet of Medical Things (IoMT) become more complicated, the
problems of divergent interests, unregulated policies, privacy and security, and the resource …

The Internet of Medical Things (IoMT) has revolutionized healthcare, but its vulnerabilities
demand robust security solutions, especially for resource-constrained devices. In this …

Smart healthcare aims to revolutionize med-ical services by integrating artificial intelligence
(AI). The limitations of classical machine learning include privacy concerns that prevent …

Cutting-edge technologies have been widely employed in healthcare delivery, resulting in
transformative advances and promising enhanced patient care, operational efficiency, and …

The Internet of Medical Things (IoMT) heralds a transformative era in healthcare, with the
potential to revolutionize patient care, healthcare services, and medical research. As with all …

Federated Learning is a collaborative machine learning paradigm that allows training
models on decentralized data while preserving data privacy. It has gained significant …