The incorporation of machine learning (ML) into healthcare information systems (IS) has
transformed multi-objective healthcare management by improving patient monitoring …

In this paper, we explore the problem of evaluating explanations in Explainable AI. While
there are some objective metrics to measure the quality of explanations, these metrics may …

The move toward artificial intelligence (AI)-native sixth-generation (6G) networks has put
more emphasis on the importance of explainability and trustworthiness in network …

Explainable artificial intelligence (XAI) has gained significant attention, especially in AI-
powered autonomous and adaptive systems (AASs). However, a discernible disconnect …

Abstract Computer Vision Systems (CVSs) have proved to be a powerful tool to evaluate the
quality of agricultural products in a non-destructive, contactless, sustainable and objective …

Fairness in machine learning (ML) has received much attention. However, existing studies
have mainly focused on the distributive fairness of ML models. The other dimension of …

In Artificial Intelligence, there is an increasing demand for adaptive models capable of
dealing with a diverse spectrum of learning tasks, surpassing the limitations of systems …

Over the last few years, Shapley value (SV), a solution concept from cooperative game
theory, has found numerous applications in data analytics (DA). This paper provides the first …

Model update is a crucial process in the operation of ML/AI systems. While updating a model
generally enhances the average prediction performance, it also significantly impacts the …

eXplainable Artificial intelligence (XAI) has grown in popularity in recent years due to the
great demand for black-box machine learning models, particularly deep neural networks …