Artificial Intelligence (AI) techniques of deep learning have revolutionized the disease
diagnosis with their outstanding image classification performance. In spite of the outstanding …

The recent surge in publications related to explainable artificial intelligence (XAI) has led to
an almost insurmountable wall if one wants to get started or stay up to date with XAI. For this …

The proposed EU regulation for Artificial Intelligence (AI), the AI Act, has sparked some
debate about the role of explainable AI (XAI) in high-risk AI systems. Some argue that black …

The rising popularity of explainable artificial intelligence (XAI) to understand high-performing
black boxes raised the question of how to evaluate explanations of machine learning (ML) …

Abstract Explainable Artificial Intelligence (XAI) has experienced a significant growth over
the last few years. This is due to the widespread application of machine learning, particularly …

Machine Learning and Artificial Intelligence (AI) more broadly have great immediate and
future potential for transforming almost all aspects of medicine. However, in many …

Abstract Previous research in Explainable Artificial Intelligence (XAI) suggests that a main
aim of explainability approaches is to satisfy specific interests, goals, expectations, needs …

In recent years, the field of explainable AI (XAI) has produced a vast collection of algorithms,
providing a useful toolbox for researchers and practitioners to build XAI applications. With …

With the rise of artificial intelligence (AI), the issue of trust in AI emerges as a paramount
societal concern. Despite increased attention of researchers, the topic remains fragmented …

Understanding black box models has become paramount as systems based on opaque
Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …