Inducing and Storing Generalised Evidences using Semantic Web formalisms

Paul, R., Groza, T. and Hunter, J,

Over the course of the last decade, decision support systems have been used to assist clinicians and researchers in expanding the body of knowledge of particular (bio)-medical areas, as well as in diverse decision-making processes (e.g., diagnosis, treatment). Creating a decision support model (e.g., a rule base) requires a set of well-established medical guidelines built on mature domain knowledge. The absence of such mature domain knowledge has hindered the development of appropriate decision support methods in the skeletal dysplasia domain. In this paper, we make the first step towards providing a solution to this issue by proposing an ontology and associated extraction algorithm that can infer generalized evidences from existing bone dysplasia patient cases. This establishes the foundation for a decision support model based on evidential reasoning, which enables semi-automated diagnosis or key disease feature extraction.

Cite as: Paul, R., Groza, T. and Hunter, J, (2012). Inducing and Storing Generalised Evidences using Semantic Web formalisms. In Proc. Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2012) Melbourne, Australia. CRPIT, 129. Butler-Henderson, K. and Gray, K. Eds., ACS. 49-58

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