Knowledge-based Processing of Medical Language: A Language Engineering Approach

In medicine large amounts of natural language documents have to be processed. Medical language is an interesting domain for the application of techniques developed in computational linguistics. Moreover, large scale applications of medical language processing raise the need to study the process of language engineering, which emphasizes some different problems than basic research. The texts found in medical applications show characteristics of a specific sublanguage that can be exploited for language processing. We present the Metexa system (Medical Text Analysis) for the analysis of radiological reports. To be able to process utterances of telegraphic style, the emphasis in system design has been put on semantic and knowledge processing components. However, a unification-based bottom-up parser is used to exploit syntactic information wherever possible. For semantic and knowledge representation a relevant part of the Conceptual Graph Theory by John Sowa has been implemented in order to yield a conceptual graph as the semantic representation of an utterance. This can be mapped e.g. to a database schema. A resolution-based inference procedure has been implemented to infer new facts from the analysed utterances.