With the rapid development of healthcare-based cyber physical systems (CPSs), more and
more healthcare data is collected from clinical institutions or hospitals. Due to the private …

Federated learning (FL) has been gaining popularity as a way to provide privacy-preserving
data sharing for the Internet of Medical Things (IoMT). As a complementary, blockchain …

The rapid growth of artificial intelligence (AI), blockchain technology, and edge computing
services have enabled the Internet of Medical Things (IoMT) to provide various healthcare …

Recently, innovations in the Internet of Medical Things (IoMT), information and
communication technologies, and machine learning (ML) have enabled smart healthcare …

In recent years, the global Internet of Medical Things (IoMT) industry has evolved at a
tremendous speed. Security and privacy are key concerns on the IoMT, owing to the huge …

Clinical trials and drug discovery would not be effective without the collaboration of
institutions. Earlier, it has been at the cost of individual's privacy. Several pacts and …

Mobile-edge computing (MEC) has been envisioned as a promising paradigm to handle the
massive volume of data generated from ubiquitous mobile devices for enabling intelligent …

The Internet of Medical Things (IoMT) has a bright future with the development of smart
mobile devices. Information technology is also leading changes in the healthcare industry …

As a distributed computing paradigm, edge computing has become a key technology for
providing timely services to mobile devices by connecting Internet of Things (IoT), cloud …

Federated learning (FL) is a promising paradigm to realize distributed machine learning on
heterogeneous clients without exposing their private data. However, there is the risk of …