OBJECTIVES: To investigate errors identified in SNOMED CT by human reviewers with help from the Abstraction Network methodology and examine why they had escaped detection by the Description Logic (DL) classifier. Case study; Two examples of errors are presented in detail (one missing IS-A relation and one duplicate concept). After correction, SNOMED CT is reclassified to ensure that no new inconsistency was introduced. CONCLUSIONS: DL-based auditing techniques built in terminology development environments ensure the logical consistency of the terminology. However, complementary approaches are needed for identifying and addressing other types of errors.
OBJECTIVES: To investigate errors identified in SNOMED CT by human reviewers with help from the Abstraction Network methodology and examine why they had escaped detection by the Description Logic (DL) classifier. Case study; Two examples of errors are presented in detail (one missing IS-A relation and one duplicate concept). After correction, SNOMED CT is reclassified to ensure that no new inconsistency was introduced. CONCLUSIONS: DL-based auditing techniques built in terminology development environments ensure the logical consistency of the terminology. However, complementary approaches are needed for identifying and addressing other types of errors.
Authors: Yue Wang; Duo Wei; Junchuan Xu; Gai Elhanan; Yehoshua Perl; Michael Halper; Yan Chen; Kent A Spackman; George Hripcsak Journal: AMIA Annu Symp Proc Date: 2008-11-06
Authors: Christopher Ochs; James Geller; Yehoshua Perl; Yan Chen; Ankur Agrawal; James T Case; George Hripcsak Journal: J Am Med Inform Assoc Date: 2014-10-20 Impact factor: 4.497
Authors: Yue Wang; Michael Halper; Duo Wei; Huanying Gu; Yehoshua Perl; Junchuan Xu; Gai Elhanan; Yan Chen; Kent A Spackman; James T Case; George Hripcsak Journal: J Biomed Inform Date: 2011-09-01 Impact factor: 6.317