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 …

In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if
harnessed appropriately, may deliver the best of expectations over many application sectors …

One of the most exciting tools that have entered the material science toolbox in recent years
is machine learning. This collection of statistical methods has already proved to be capable …

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 deep …

Saliency methods have emerged as a popular tool to highlight features in an input deemed
relevant for the prediction of a learned model. Several saliency methods have been …

Artificial intelligence (AI) and machine learning (ML) have come a long way from the earlier
days of conceptual theories, to being an integral part of today's technological society. Rapid …

Symbolic regression (SR) is an approach of interpretable machine learning for building
mathematical formulas that best fit certain datasets. In this work, SR is used to guide the …

In a short period of time, many areas of science have made a sharp transition towards data-
dependent methods. In some cases, this process has been enabled by simultaneous …

Background With the rapid adoption of electronic health records (EHRs), it is desirable to
harvest information and knowledge from EHRs to support automated systems at the point of …

In information societies, operations, decisions and choices previously left to humans are
increasingly delegated to algorithms, which may advise, if not decide, about how data …