There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …

As data privacy increasingly becomes a critical societal concern, federated learning has
been a hot research topic in enabling the collaborative training of machine learning models …

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 …

Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …

Over the last decade, smart cities (SC) have been developed worldwide. Implementing big
data and the internet of things improves the monitoring and integration of different …

Abstract Internet of Medical Things (IoMT) supports traditional healthcare systems by
providing enhanced scalability, efficiency, reliability, and accuracy of healthcare services. It …

Given its advantages in low latency, fast response, context-aware services, mobility, and
privacy preservation, edge computing has emerged as the key support for intelligent …

With the advent of machine learning (ML) and deep learning (DL) empowered applications
for critical applications like healthcare, the questions about liability, trust, and interpretability …

The increasing need for economic, safe, and sustainable smart manufacturing combined
with novel technological enablers has paved the way for artificial intelligence (AI) and big …

Federated learning is the process of developing machine learning models over datasets
distributed across data centers such as hospitals, clinical research labs, and mobile devices …