As advances in artificial intelligence (AI) continue to transform and revolutionize the field of
medicine, understanding the potential uses of generative AI in health care becomes …

Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm enabling
multiple parties to train a model collaboratively without sharing their data. With the upcoming …

The Internet of Things (IoT) has significantly impacted the evolution of consumer-oriented
smart environments, primarily due to its capacity for transformative device-to-device …

This research paper explores the transformative potential of federated learning in healthcare
informatics, focusing on its pivotal role in balancing advancements with privacy and security …

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 …

Abstract The Artificial Intelligence of Things (AIoT), a combination of the Internet of Things
(IoT) and Artificial Intelligence (AI), plays an increasingly important role in smart agriculture …

Federated Learning (FL) is an increasingly popular form of distributed machine learning that
addresses privacy concerns by allowing participants to collaboratively train machine …

Federated learning (FL) is a popular solution for distributed machine learning (ML). While FL
has traditionally been studied for supervised ML tasks, in many applications, it is impractical …

Abstract Internet of Medical Things (IoMT) can be leveraged for periodic sensing and
recording of different health parameters using sensors, wireless communications, and …

Introduction In recent years, the proliferation of Industrial Internet of Things (IIoT) devices has
resulted in a substantial increase in data generation across various domains, including the …