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 usefuln
ess 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 evaluat
ed lists of related terms suggested by different thesauri for 12 different
directed searches in the CANCERLIT testbed. The preliminary results indicat
ed that among the thesauri, there were no statistically significant differe
nces in either term recall or precision. Surprisingly, there was almost no
overlap of relevant terms suggested by the different thesauri for a given s
earch. This suggests that recall could be significantly improved by using a
combined thesaurus approach. (C) 2000 Elsevier Science B.V. All rights res
erved.