Due to market deregulation and globalisation, competitive environments in various sectors
continuously evolve, leading to increased customer churn. Effectively anticipating and …

This study investigates the impact of machine learning models on the generation of
counterfactual explanations by conducting a benchmark evaluation over three different types …

The rapid progress of research aimed at interpreting the inner workings of advanced
language models has highlighted a need for contextualizing the insights gained from years …

Manual verification has become very challenging based on the increasing volume of
information shared online and the role of generative Artificial Intelligence (AI). Thus, AI …

Genetic programming (GP) has the potential to generate explainable results, especially
when used for dimensionality reduction. In this research, we investigate the potential of …

This study introduces an efficient methodology for addressing fault detection, classification,
and severity estimation in rolling element bearings. The methodology is structured into three …

Deceptive artificial intelligence (AI) is a heavily loaded term. Its semantic load has become
exponentially heavier in a very short period of time. Perhaps, most of this semantic load, at …

Early-stage Alzheimer's disease (AD) and frontotemporal dementia (FTD) share similar
symptoms, complicating their diagnosis and the development of specific treatment …

Large Language Models (LLMs) are predictive probabilistic models capable of passing
several professional tests at a level comparable to humans. However, these capabilities …

Abstract Background and Objective: Artificial Intelligence (AI) has shown significant
advancements across several industries, including healthcare, using better fusion …