An Exposition of Uncertain Reasoning Based Analysis: An Investigation of Total Hip Arthroplasty

Abstract

Uncertain reasoning is closely associated with the pertinent analysis of data where there may be imprecision, inexactness, and uncertainty in its information content. In computer modelling, this should move any analysis to be inclusive of such potential uncertainty, away from the presumption of perfect data to be worked with. The nascent Classification and Ranking Belief Simplex (CaRBS) technique employed in this chapter enables analysis in the spirit of uncertain reasoning. The operational rudiments of the CaRBS technique are based on the Dempster-Shafer theory of evidence, affording the presence of ignorance in any analysis undertaken. An investigation of Total Hip Arthraplasty (THA), concerned with hip replacements, forms the applied problem around which the uncertain reasoning based analysis using CaRBS is exposited. The presented findings include the levels of fit in constructed models, and the contribution of features within the models. Where appropriate, numerical calculations are shown, to illustrate this novel form of analysis.