We seek to examine the use of an image processing pipeline on Magnetic Resonance
Imaging (MRI) to identify features of Focal Cortical Dysplasia (FCD) in children who were …

In diagnostic causal reasoning, the goal is to infer the probability of causes from one or
multiple observed effects. Typically, studies investigating such tasks provide subjects with …

Within the domain of psychology, Optimal Experimental Design (OED) principles have been
used to model how people seek and evaluate information. Despite proving valuable as …

The curse of dimensionality, which has been widely studied in statistics and machine
learning, occurs when additional features cause the size of the feature space to grow so …

The key challenge in text classification techniques is the overall performance. In this paper
we discuss the need of using parallel/distributed data mining algorithms for text …

This chapter discusses diagnostic reasoning from the perspective of causal inference. The
computational framework that provides the foundation for the analyses—probabilistic …

A probabilistic causal chain A→ B→ C may intuitively appear to be transitive: If A
probabilistically causes B, and B probabilistically causes C, A probabilistically causes C …

In text mining, clustering and classification are the most important techniques to extract
information from textual data. These are techniques which allow us to identify similar groups …

In this paper, we introduce the first application of the belief propagation algorithm in the
design and evaluation of trust management systems with an introduction of a novel …

The human mind has developed numerous cognitive tools to allow us to navigate the
uncertainty of the world and make sense of situations and events. In this thesis I present a …