SNOMED CT 용어체계에서 형제 개념의 속성 관계를 활용한 누락 개념 탐지 기법
Identifying Missing Concepts in SNOMED CT by Utilizing Attribute Relationships of Sibling Concepts
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SNOMED CT 용어체계는 전 세계적으로 가장 널리 사용되는 포괄적 임상 용어체계이다. 하지만용어체계의 방대함 및 의학 지식의 지속적 증가로 인해 용어체계를 구성하는 개념 또는 관계의 누락, 계층 구조의 오류 등 구조적 부정확성 및 불일치 문제가 존재한다. 본 논문에서는 용어체계의 일관성을 높이기 위해 개념에 연결된 속성을 이용하여 잠재적으로 누락된 개념을 탐지하는 방법을 제안한다. 제안하는 방법은 개념이 가지고 있는 속성 관계의 특성을 분석하고 동일한 특성을 공유하는형제 개념들을 추출한 후 부모 개념들이 해당 특성들을 반영하는지 여부를 평가하여 잠재적으로 누락된 개념을 탐지한다. 제안하는 방법을 2023년 3월 SNOMED CT 국제 배포판에 적용하여 분석한결과 형제 개념들의 공통 속성을 부모 개념이 반영하지 못하는 경우를 564건 발견하였으며, 다중 부모 개념을 포함하는 경우를 도출하여 총 384개의 잠재적 누락 개념을 탐지하였다.
Abstract
SNOMED CT is the most widely used comprehensive clinical terminology system worldwide. However, due to the vastness of the terminology and the continuous growth of medical knowledge, the system involve quality issues such as structural inaccuracies and inconsistencies, including missing concepts or relationships and hierarchical errors. In this paper, we propose a method to enhance the consistency of the system by detecting potentially missing concepts by utilizing attributes linked to concepts. The proposed method analyzes the characteristics of the attribute relationships of concepts, extracts sibling concepts that share the same characteristics, and then evaluates whether the parent concepts reflect these characteristics to detect potentially missing concepts. By applying this method to the March 2023 SNOMED CT international release, we identified 564 instances where parent concepts did not reflect the common attributes of their sibling concepts, and a total of 384 potentially missing concepts were detected, including cases involving multiple parent concepts.
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