E-resources
-
Abeysinghe, Rashmie; Zheng, Fengbo; Hinderer, Eugene W.; Moseley, Hunter N. B.; Cui, Licong
2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2018-Dec.Conference Proceeding
We introduce a lexical-based inference approach for identifying subtype (or is_{-}a relation) inconsistencies in biomedical terminologies. Given a terminology, we first represent the name of each concept in the terminology as a sequence of words. We then generate hierarchically-linked and-unlinked pairs of concepts, such that the two concepts in a pair have the same number of words, and contain at least one word in common and a fixed number n of different words (n = 1,2,3,4,5). The linked and unlinked concept-pairs further infer corresponding linked and unlinked term-pairs, respectively. If a linked concept-pair and an unlinked concept-pair infer the same term-pair, we consider this as a potential subtype inconsistency, which may indicate a missing subtype relation or an incorrect subtype relation. We applied this approach to Gene Ontology (GO), National Cancer Institute thesaurus (NCIt) and SNOMED CT. A total of 4,841 potential subtype inconsistencies were found in GO, 2,677 in NCIt, and 53,782 in SNOMED CT. Domain experts evaluated a random sample of 211 potential inconsistencies in GO, and verified that 124 of them are valid (\mathrm {i}.\mathrm {e}., a precision of 58.77% for detecting subtype inconsistencies in GO). We also performed a preliminary study on the extent to which external knowledge in the Unified Medical Language System (UMLS) can provide supporting evidence for validating the detected potential inconsistencies: 0.54% (=26/4841) for GO, 11.43% (=306/2677) for NCIt, and 3.61% (=1940/53782) for SNOMED CT. Results indicate that our lexical-based inference approach is a promising way to identify subtype inconsistencies and facilitates the quality improvement of biomedical terminologies.
![loading ... loading ...](themes/default/img/ajax-loading.gif)
Shelf entry
Permalink
- URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year | Impact factor | Edition | Category | Classification | ||||
---|---|---|---|---|---|---|---|---|
JCR | SNIP | JCR | SNIP | JCR | SNIP | JCR | SNIP |
Select the library membership card:
If the library membership card is not in the list,
add a new one.
DRS, in which the journal is indexed
Database name | Field | Year |
---|
Links to authors' personal bibliographies | Links to information on researchers in the SICRIS system |
---|
Source: Personal bibliographies
and: SICRIS
The material is available in full text. If you wish to order the material anyway, click the Continue button.