With the recent advances in the field of artificial intelligence, an increasing number of
decision-making tasks are delegated to software systems. A key requirement for the success …

Bayesian networks (BNs), also known as Bayesian belief networks or Bayes nets, are a kind
of probabilistic graphical model that has become very popular to practitioners mainly due to …

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are
growing in popularity. Their versatility and modelling power is now employed across a …

Bayesian networks (BNs) and influence diagrams (IDs) are probabilistic graphical models
that are widely used for building diagnosis-and decision-support expert systems …

1 BACKGROUND The personalized selection and presentation of content have become
common in today's online world, for example on media streaming sites, e-commerce shops …

Background Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer
and the most difficult to predict. When there are no distant metastases, the optimal therapy …

In the original formulation of influence diagrams (IDs), each model contained exactly one
utility node. Tatman and Shachter (1990)[4], introduced the possibility of having super value …

OpenMarkov is a Java open-source tool for building and evaluating probabilistic graphical
models, including Bayesian networks, influence diagrams, and some Markov models. With …

This paper presents decision analysis networks (DANs) as a new type of probabilistic
graphical model. Like influence diagrams (IDs), DANs are much more compact and easier to …

The paper aims to propose an Expert System to predict the failure of onshore pipelines.
Knowledge Management supports expertise sharing throughout the organization. The …