The fusion of statistical and AI Methodologies for interpreting uncertainty in healthcare

This thesis presents a synthesis of themes from the works published in the period between 2018-2022 in collaboration with colleagues from Queen’s University Belfast (UK) and Ontario Tech University (Canada) with the goal to present novel methodologies resulting from a fusion of statistical and AI techniques, the purpose of which is in aiding healthcare stakeholders in their decision making by minimising the negative effect of uncertainty.

There are 7 publications in total that are forming the body of work of this thesis, of which 4 are journal articles, 2 are book chapters and 1 is in conference proceedings. Rather than present the papers in chronological order, they are included in the thesis where they are naturally best placed to suit the flow of the narrative. The main body of work, provides the detailed contributions that the publications have made to the statistics, computer science, health informatics and public health domains.