Predictions obtained by, eg, artificial neural networks have a high accuracy but humans
often perceive the models as black boxes. Insights about the decision making are mostly …

Deep learning (DL) models have achieved impressive performance in various domains such
as medicine, finance, and autonomous vehicle systems with advances in computing power …

Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and
progression detection have been intensively studied. Nevertheless, research studies often …

A key challenge in developing and deploying Machine Learning (ML) systems is
understanding their performance across a wide range of inputs. To address this challenge …

Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

The growing success of Machine Learning (ML) is making significant improvements to
predictive models, facilitating their integration in various application fields. Despite its …

We propose a framework for interactive and explainable machine learning that enables
users to (1) understand machine learning models;(2) diagnose model limitations using …

The quest to open black box artificial intelligence (AI) systems evolved into an emerging
phenomenon of global interest for academia, business, and society and brought about the …

Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

While anomaly detection is relatively well-studied, it remains a topic of ongoing interest and
challenge, as our society becomes increasingly interconnected and digitalized. In this paper …