An Automated Approach For Identifying Erroneous Is-A Relations In SNOMED CT

Authors

Language

English

Publication Date

1-1-2024

Journal

AMIA Summits on Translational Science Proceedings

PMID

38827070

PMCID

PMC11141797

PubMedCentral® Posted Date

July 2023

PubMedCentral® Full Text Version

Post-print

Abstract

SNOMED CT is the most comprehensive clinical terminology employed worldwide and enhancing its accuracy is of utmost importance. In this work, we introduce an automated approach to identifying erroneous IS-A relations in SNOMED CT. We first extract linked concept-pairs from which we generate Term Difference Pairs (TDPs) that contain differences between the concepts. Given a TDP, if the reversed TDP also exists and the number of linked-pairs generating this TDP is less than those generating the reversed TDP, then we suggest the former linked-pairs as potentially erroneous IS-A relations. We applied this approach to the Clinical finding and Procedure subhierarchies of the 2022 March US Edition of SNOMED CT, and obtained 52 potentially erroneous IS-A relations and a candidate list of 48 linked-pairs. A domain expert confirmed 41 out of 52 (78.8%) are valid and identified 26 erroneous IS-A relations out of 48 linked-pairs demonstrating the effectiveness of the approach.

Published Open-Access

yes

Recommended Citation

, "An Automated Approach For Identifying Erroneous Is-A Relations In SNOMED CT" (2024). Faculty, Staff and Student Publications. 130.
https://digitalcommons.library.tmc.edu/uthshis_docs/130