We describe a natural language processing system (Enhanced SemRep) to identify core assertions on pharmacogenomics in Medline citations. Extracted information is represented as semantic predications covering a range of relations relevant to this domain. The specific relations addressed by the system provide greater precision than that achievable with methods that rely on entity co-occurrence. The development of Enhanced SemRep is based on the adaptation of an existing system and crucially depends on domain knowledge in the Unified Medical Language System. We provide a preliminary evaluation (55% recall and 73% precision) and discuss the potential of this system in assisting both clinical practice and scientific investigation.
%0 Conference Paper
%1 Ahlers07extractingsemantic
%A Ahlers, Caroline B.
%A Fiszman, Marcelo
%A Demner-fushman, Dina
%A michel Lang, François
%A Rindflesch, Thomas C.
%B In Proc. Pacific Symposium on Biocomputing
%D 2007
%K CAT CAT-REL-NLP CAT-REL-RULE pharmacogenomics predictions semantic semrep
%P 209--220
%T Extracting semantic predications from MEDLINE citations for pharmacogenomics
%U http://psb.stanford.edu/psb-online/proceedings/psb07/abstracts/2007_p209.html
%X We describe a natural language processing system (Enhanced SemRep) to identify core assertions on pharmacogenomics in Medline citations. Extracted information is represented as semantic predications covering a range of relations relevant to this domain. The specific relations addressed by the system provide greater precision than that achievable with methods that rely on entity co-occurrence. The development of Enhanced SemRep is based on the adaptation of an existing system and crucially depends on domain knowledge in the Unified Medical Language System. We provide a preliminary evaluation (55% recall and 73% precision) and discuss the potential of this system in assisting both clinical practice and scientific investigation.
@inproceedings{Ahlers07extractingsemantic,
abstract = {We describe a natural language processing system (Enhanced SemRep) to identify core assertions on pharmacogenomics in Medline citations. Extracted information is represented as semantic predications covering a range of relations relevant to this domain. The specific relations addressed by the system provide greater precision than that achievable with methods that rely on entity co-occurrence. The development of Enhanced SemRep is based on the adaptation of an existing system and crucially depends on domain knowledge in the Unified Medical Language System. We provide a preliminary evaluation (55% recall and 73% precision) and discuss the potential of this system in assisting both clinical practice and scientific investigation.},
added-at = {2010-06-16T08:54:20.000+0200},
author = {Ahlers, Caroline B. and Fiszman, Marcelo and Demner-fushman, Dina and michel Lang, François and Rindflesch, Thomas C.},
biburl = {https://www.bibsonomy.org/bibtex/23dd0f9f2c6bd2f77637edab085fb5d86/huiyangsfsu},
booktitle = {In Proc. Pacific Symposium on Biocomputing},
interhash = {74a2fae49829c39a2c74997e54fda963},
intrahash = {3dd0f9f2c6bd2f77637edab085fb5d86},
keywords = {CAT CAT-REL-NLP CAT-REL-RULE pharmacogenomics predictions semantic semrep},
pages = {209--220},
timestamp = {2010-11-12T00:58:08.000+0100},
title = {Extracting semantic predications from MEDLINE citations for pharmacogenomics},
url = {http://psb.stanford.edu/psb-online/proceedings/psb07/abstracts/2007_p209.html},
year = 2007
}