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

Deep neural networks (DNNs) are currently being deployed as machine learning technology
in a wide range of important real-world applications. DNNs consist of a huge number of …

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 …

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 The Intelligent Transport System (ITS) is an emerging paradigm that offers
numerous services at the infrastructure level for vehicle applications. Vehicle-to …

Feature selection is one of the crucial data preprocessing techniques for improving the
performance of machine learning (ML) models. Recently, metaheuristic feature selection …

The rapid expansion of the Internet of Things (IoT) and Edge Computing has presented
challenges for centralized Machine and Deep Learning (ML/DL) methods due to the …

The fusion of blockchain and artificial intelligence (AI) marks a paradigm shift in healthcare,
addressing critical challenges in securing electronic health records (EHRs), ensuring data …

Federated Learning (FL) has recently arisen as a revolutionary approach to collaborative
training Machine Learning models. According to this novel framework, multiple participants …

Utilizing digital healthcare services for patients who use wheelchairs is a vital and effective
means to enhance their healthcare. Digital healthcare integrates various healthcare …