Auditing the UMLS for redundant classifications.

The UMLS's Semantic Network (SN) serves as a valuable abstraction for the underlying concept repository called the Metathesaurus (META). Specifically, the SN forms a classification layer for the META, with each of the META's constituent concepts assigned to one or more semantic types in the SN. The rule in the design of the SN is to have concepts explicitly assigned to the lowest possible semantic types in the SN's IS-A hierarchy. Implicit assignment to higher semantic types can be inferred via the IS-A relationships. However, in subsequent versions of the UMLS, unnecessary, simultaneous assignments to descendant and ancestor semantic types have been discovered (e.g., 8,622 in the UMLS 1998 version and 12,657 in the 2001 version). The assignment of concepts to such ancestor semantic types is called redundant classification. There is a need for an automated auditing tool that can identify all these redundant classifications. In this paper, an efficient algorithm for this auditing task is introduced. Details of its application to the current (2001) version of the UMLS are presented and the results are discussed.

Enriching the structure of the UMLS semantic network.

The Unified Medical Language System's (UMLS's) Semantic Network (SN)---consisting of a network of semantic types---has a two-tree structure, where each semantic type has at most one parent semantic type. This arrangement is restrictive because some semantic types are, by their definition, specializations of several parents. As a proposed enhancement to the SN, its semantic types have previously been partitioned into groups, each of which contains semantic types of some specific area. However, some groups of this proposed partition contain forest (i.e., multiple-tree) structures or even isolated semantic types. Both situations imply a disconnected internal structure. Connectivity is actually one way to assess the proposed "semantic validity" principle for partitions. It is a desired, although not required, property. In this paper, we introduce a methodology for identifying "missing" IS-A links and adding them to the SN. This process transforms the SN into a Directed Acyclic Graph (DAG) structure, with semantic types permitted to have multiple parents. A result of our methodology is the transformation of the proposed SN partition into groups satisfying the connectivity property.