Exploring the use of concept spaces to improve medical information retrieval

Abstract

This research investigated the application of techniques successfully used in previous information retrieval research, to the more challenging area of medical informatics. It was performed on a biomedical document collection testbed, CANCERLIT, provided by the National Cancer Institute (NCI) , which contains information on all types of cancer therapy. The quality or usefulness of terms suggested by three different thesauri, one based on MeSH terms, one based solely on terms from the document collection, and one based on the Unified Medical Language System UMLS Metathesaurus, was explored with the ultimate goal of improving CANCERLIT information search and retrieval. Researchers affiliated with the University of Arizona Cancer Center evaluated lists of related terms suggested by different thesauri for 12 different directed searches in the CANCERLIT testbed. The preliminary results indicated that among the thesauri, there were no statistically significant differences in either term recall or precision. Surprisingly, there was almost no overlap of relevant terms suggested by the different thesauri for a given search. This suggests that recall could be significantly improved by using a combined thesaurus approach.