Bean, C.A.: Representation of medical knowledge for automated semantic interpretation of clinical reports (2004)
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- Abstract
- A set of cardiac catheterisation case reports was analysed to identify and encode for automated interpretation of the semantic indicators of location and severity of disease in coronary arteries. Presence of disease was indicated by the use of specific or general disease terms, typically with a modifier, while absence of disease was indicated by negation of similar phrases. Disease modifiers indicating severity could be qualitative or quantitative, and a 7-point severity scale was devised to normalise these modifiers based an relative clinical significance. Location of disease was indicated in three basic ways: By situation in arbitrary topographic divisions, by situation relative to a named structure, or by using named structures as boundary delimiters to describe disease extent. In addition, semantic indicators were identified for such topological relationships as proximity, contiguity, overlap, and enclosure. Spatial reasoning was often necessary to understand the specific localisation of disease, demonstrating the need for a general Spatial extension to the underlying knowledge base.
