Interpretable machine learning aims at unveiling the reasons behind predictions returned by
uninterpretable classifiers. One of the most valuable types of explanation consists of …

Machine learning is increasingly used to inform decision making in sensitive situations
where decisions have consequential effects on individuals' lives. In these settings, in …

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 Machine learning plays a role in many deployed decision systems, often in ways
that are difficult or impossible to understand by human stakeholders. Explaining, in a human …

A number of algorithms in the field of artificial intelligence offer poorly interpretable
decisions. To disclose the reasoning behind such algorithms, their output can be explained …

Abstract Current advances in Artificial Intelligence (AI) and Machine Learning have achieved
unprecedented impact across research communities and industry. Nevertheless, concerns …

Deep learning models have achieved high performance across different domains, such as
medical decision-making, autonomous vehicles, decision support systems, among many …

Machine learning is increasingly used to inform decision-making in sensitive situations
where decisions have consequential effects on individuals' lives. In these settings, in …

Machine learning plays a role in many deployed decision systems, often in ways that are
difficult or impossible to understand by human stakeholders. Explaining, in a human …

We are witnessing a fast development of Artificial Intelligence (AI), but it becomes
dramatically challenging to explain AI models in the past decade.“Explanation” has a flexible …