title: A model for medical knowledge representation application to the analysis of descriptive pathology reports.
abstract: A new knowledge-representation system is presented, designed for medical knowledge-based applications and in particular for the analysis of descriptive medical reports. Knowledge is represented at two levels. A definitional level uses a concept-type hierarchy, a relation-type hierarchy, and a set of schematic graphs to define the concepts used and the relations between them, as well as different types of cardinality restrictions on these relations. A set of compositional hierarchies using the classic "has-part" relation as well as a new set-inclusion relation allows concept composition to be precisely defined. An assertional level allows the creation and manipulation of empirical data, in the form of graphs using the concepts, relations, and constraints defined at the definition level. The use of cardinality constraints in graph unification is considered in the context of descriptive medical discourse analysis.
mesh_terms: D001185:Artificial Intelligence; D003196:Computer Graphics; D006801:Humans; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D010338:Pathology, Clinical