TY - JOUR
T1 - Effectively processing medical term queries on the UMLS Metathesaurus by layered dynamic programming
AU - Ren, Kaiyu
AU - Lai, Albert M.
AU - Mukhopadhyay, Aveek
AU - Machiraju, Raghu
AU - Huang, Kun
AU - Xiang, Yang
N1 - Funding Information:
AL and AM were supported by award number R01LM011116 from the National Library of Medicine. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Library of Medicine or the National Institutes of Health. KH was supported in part by the Department of Defense CDMRP Grant (CA100865).
Funding Information:
Publication of this article was funded by the Department of Biomedical Informatics, The Ohio State University, USA. This article has been published as part of BMC Medical Genomics Volume 7 Supplement 1, 2014: Selected articles from the 3rd Translational Bioinformatics Conference (TBC/ISCB-Asia 2013). The full contents of the supplement are available online at http://www.biomedcentral.com/ bmcmedgenomics/supplements/7/S1.
PY - 2014/5/8
Y1 - 2014/5/8
N2 - Background: Mapping medical terms to standardized UMLS concepts is a basic step for leveraging biomedical texts in data management and analysis. However, available methods and tools have major limitations in handling queries over the UMLS Metathesaurus that contain inaccurate query terms, which frequently appear in real world applications. Methods. To provide a practical solution for this task, we propose a layered dynamic programming mapping (LDPMap) approach, which can efficiently handle these queries. LDPMap uses indexing and two layers of dynamic programming techniques to efficiently map a biomedical term to a UMLS concept. Results: Our empirical study shows that LDPMap achieves much faster query speeds than LCS. In comparison to the UMLS Metathesaurus Browser and MetaMap, LDPMap is much more effective in querying the UMLS Metathesaurus for inaccurately spelled medical terms, long medical terms, and medical terms with special characters. Conclusions: These results demonstrate that LDPMap is an efficient and effective method for mapping medical terms to the UMLS Metathesaurus.
AB - Background: Mapping medical terms to standardized UMLS concepts is a basic step for leveraging biomedical texts in data management and analysis. However, available methods and tools have major limitations in handling queries over the UMLS Metathesaurus that contain inaccurate query terms, which frequently appear in real world applications. Methods. To provide a practical solution for this task, we propose a layered dynamic programming mapping (LDPMap) approach, which can efficiently handle these queries. LDPMap uses indexing and two layers of dynamic programming techniques to efficiently map a biomedical term to a UMLS concept. Results: Our empirical study shows that LDPMap achieves much faster query speeds than LCS. In comparison to the UMLS Metathesaurus Browser and MetaMap, LDPMap is much more effective in querying the UMLS Metathesaurus for inaccurately spelled medical terms, long medical terms, and medical terms with special characters. Conclusions: These results demonstrate that LDPMap is an efficient and effective method for mapping medical terms to the UMLS Metathesaurus.
UR - http://www.scopus.com/inward/record.url?scp=84900460214&partnerID=8YFLogxK
U2 - 10.1186/1755-8794-7-S1-S11
DO - 10.1186/1755-8794-7-S1-S11
M3 - Article
C2 - 25079259
AN - SCOPUS:84900460214
SN - 1755-8794
VL - 7
JO - BMC Medical Genomics
JF - BMC Medical Genomics
IS - SUPPL.1
M1 - S11
ER -