Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4942197 | Artificial Intelligence in Medicine | 2017 | 6 Pages |
Abstract
Overlapping concepts from Uberon's disjoint abstraction network are quite likely (up to 28.9%) to exhibit issues. The results suggest that the methodology can transfer well between same family ontologies. Although Uberon exhibited relatively few overlapping concepts, the methodology can be combined with other semantic indicators to expand the process to other concepts within the ontology that will generate high yields of discovered issues.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Gai Elhanan, Christopher Ochs, Jose L.V. Jr., Hao Liu, Christopher J. Mungall, Yehoshua Perl,