Deep neural networks (DNN) have remarkably progressed in applications involving large
and complex datasets but have been criticized as a black-box. This downside has recently …

Explainability is a hot topic nowadays for artificial intelligent (AI) systems. The role of
machine learning (ML) models on influencing human decisions shed light on the back-box …

Globally, lung cancer has a high fatality rate and is a lethal disease. Since lung cancer
affects both men and women, it requires extra consideration when evaluating various …

Companies aim to offer customized treatments, intelligent care, and a seamless experience
to their customers. Interactions between a company and its customers largely depend on the …

Brain tumor classification is a significant issue in Computer-Aided Diagnosis (CAD) for
clinical applications. The classification process is crucial and plays a major role to diagnosis …

A key challenge in artificial intelligence is the well-known tradeoff between the
interpretability of an algorithm, and its accuracy. Designing interpretable, highly accurate AI …

The emerging success of Deep Learning (DL) in various application areas comes also with
the questions starting with" How" s and" Why" s. These questions can be answered if the DL …

A key challenge in eXplainable Artificial Intelligence is the well-known tradeoff between the
transparency of an algorithm (ie, how easily a human can directly understand the algorithm …

The Internet of Things (IoT) has significantly enhanced various aspects of our daily lives,
including security, health, education, and energy efficiency, among others. Within the realm …

The approach to calculating density significantly impacts the clustering efficacy of the
Density Peak Clustering (DPC) method, with various density calculation methods tailored for …