Session:

Mini-Symposia: Computational Medicine Building and Applying Intelligent Systems in Health
Tuesday, March 02, 2004, 17.15 – 17.35

Session Chair:

Peter Kokol

Paper Title:

Boosting the Medical Knowledge Infrastructure — A Feasibility Study on Very Large Terminological Knowledge Bases

Author(s):

U. Hahn, Text Knowledge Engineering Lab, Albert-Ludwigs-Universitat Freiburg, Germany
S. Schulz, Medical Informatics Department, Universitatsklinikum Freiburg, Germany

Abstract:

We conducted a feasibility study in which conceptual knowledge was extracted from an informal medical thesaurus (UMLS) and automatically converted into a formally sound description logics system. Our approach consists of four steps: concept definitions are automatically generated from the UMLS source, integrity checking of taxonomic and partonomic hierarchies is performed by the terminological classifier, cycles and inconsistencies are eliminated, and incremental refinement of the evolving knowledge base is performed by a domain expert. We report on experiments with a very large terminological knowledge base composed of 164,000 concepts and 76,000 relations.