The benefits and drawbacks of various technologies, as well as the scope of their
application, are thoroughly discussed. The use of anonymity technology and differential …

Artificial intelligence (AI) has led to a high rate of development in healthcare, and good
progress has been made on many complex medical problems. However, there is a lack of …

Federated learning (FL) provides a distributed machine learning system that enables
participants to train using local data to create a shared model by eliminating the requirement …

The domain of healthcare data collaboration heralds an era of profound transformation,
underscoring an exceptional potential to elevate the quality of patient care and expedite the …

Every individual in our technologically evolved world needs proper data security. The
procedure of exchanging medical information is increasingly concerned with data privacy …

The paper presents a brief introduction to big data and its role in healthcare applications. It is
observed that the use of big data architecture and techniques are continuously assisting in …

Big data analytics has anonymously changed the overall global scenario to discover
knowledge trends for future decision making. In general, potential area of big data …

Data have always been a major priority for businesses of all sizes. Businesses tend to
enhance their ability in contextualizing data and draw new insights from it as the data itself …

Federated learning preserves the privacy of user data through Machine Learning (ML). It
enables the training of an ML model during this process. The Healthcare Internet of Things …

This research focuses on addressing the privacy issues in healthcare advancement
monitoring with the rapid establishment of the decentralised communication system in the …