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 …

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

The Healthcare industry demands increased privacy and security to protect confidential
patient information and comply with regulations. Both these features can be incorporated …

Recently, more than 80% of sudden cardiac death is caused by arrhythmia, whose
incidence has increased rapidly. In the actual wearable device acquisition process, ECG …

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 Machine learning with considering data privacy-preservation and personalized
models has received attentions, especially in the manufacturing field. The data often exist in …

As data sharing on the Internet of Medical Things (IoMT) become more complicated, the
problems of divergent interests, unregulated policies, privacy and security, and the resource …

Decentralized federated learning integrates advanced technologies, including distributed
computing and secure encryption methodologies, to facilitate a robust and efficient …