Disambiguation of biomedical text using diverse sources of information.
BACKGROUND
Like text in other domains, biomedical documents contain a range of terms with more than one possible meaning. These ambiguities form a significant obstacle to the automatic processing of biomedical texts. Previous approaches to resolving this problem have made use of various sources of information including linguistic features of the context in which the ambiguous term is used and domain-specific resources, such as UMLS.


METHODS
We compare various sources of information including ones which have been previously used and a novel one: MeSH terms. Evaluation is carried out using a standard test set (the NLM-WSD corpus).


RESULTS
The best performance is obtained using a combination of linguistic features and MeSH terms. Performance of our system exceeds previously published results for systems evaluated using the same data set.


CONCLUSIONS
Disambiguation of biomedical terms benefits from the use of information from a variety of sources. In particular, MeSH terms have proved to be useful and should be used if available.
Stevenson
Mark
M
Department of Computer Science, University of Sheffield, Regent Court, 211 Portobello, Sheffield S14DP, UK. m.stevenson@dcs.shef.ac.uk
Guo
Yikun
Y
Gaizauskas
Robert
R
Martinez
David
D
D000465:Algorithms; D001185:Artificial Intelligence; D016206:Databases, Bibliographic; D004282:Documentation / Q000379:methods*; D016247:Information Storage and Retrieval; D008037:Linguistics; D016239:MEDLINE; D046650:Medical Subject Headings; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D009626:Terminology as Topic; D017432:Unified Medical Language System