基于自底向上自然语言处理的 UMLS 作为计算机可解释指南本体语义源适用性评估。
Bottom-Up Natural Language Processing Based Evaluation of the Fitness of UMLS as a Semantic Source for a Computer Interpretable Guidelines Ontology.
机构信息
Institute of Digital Healthcare, WMG, University of Warwick, UK.
Department of Computer Science, Edge Hill University, UK.
出版信息
Stud Health Technol Inform. 2022 Jun 6;290:1060-1061. doi: 10.3233/SHTI220267.
BACKGROUND
CIGs languages consist of approach specific concepts. More widely used concepts, such as those in UMLS are not typically used.
OBJECTIVE
An evaluation of UMLS concept sufficiency for CIG definition.
METHOD
A popular guideline is mapped to UMLS concepts with NLP. Results are reviewed to evaluate gaps, and appropriateness.
RESULTS
A significant number of the guideline text mapped to UMLS concepts.
CONCLUSIONS
The approach has shown promise and highlighted further challenges.
背景
CIGs 语言包含特定于方法的概念。通常不使用 UMLS 中那些使用更为广泛的概念。
目的
评估 UMLS 概念对于 CIG 定义的充分性。
方法
使用自然语言处理技术将一个流行的指南映射到 UMLS 概念。对结果进行审查，以评估差距和适当性。
结果
指南文本的很大一部分映射到 UMLS 概念。
结论
该方法显示出了前景，并突出了进一步的挑战。
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