Associating semantic grammars with the SNOMED: processing medical language and representing clinical facts into a language-independent frame.

We describe one approach for natural language processing of medical texts that associates a semantic grammar with the SNOMED (Systematized Nomenclature of Medicine). Our research hypothesis is that the combination of the nomenclature's declarative knowledge with a formal grammar would create a scientific sublanguage embedded with medical knowledge that could be used for analyzing and formatting medical texts. This combination permitted the abstraction of templates we call "semantic patterns." These patterns represent both linguistic and medical knowledge, packed into a hybrid information format. We analyzed manually case reports described in the New England Journal of Medicine (NEJM) from 1985 to 1988 and extracted empirically a semantic grammar. Over 2,000 sentences were analyzed. About 160 structural semantic patterns were abstracted and included in the database of one parser. We tested the parser using reports from 1989 to 1990. Results show that this approach is efficient for processing, indexing, and structuring diverse parts of case reports narrative. The analyzed medical sentences are structured into a language-independent semantic frame format. We conclude that the association of semantic grammars with the SNOMED enabled the construction of a formal system for analysis and representation of clinical facts. The transformation of the structured information from its frame format into other representational schemes, like conceptual graphs, is straightforward. Another application includes the use of the formatted language-independent frame for telegraphic English-Japanese translations of medical sentences.