Pirogov Russian National Research Medical University.
Stud Health Technol Inform. 2023 Jun 29;305:186-189. doi: 10.3233/SHTI230458.
Clinical search engines development is actual task for medical informatics. The main issue in this area is to implement high-quality unstructured texts processing. Ontological interdisciplinary metathesaurus UMLS can be used to solve this problem. Currently, there is no unified method to relevant information aggregation from UMLS. In this research, we have presented the UMLS as graph model and performed the spot check of UMLS structure to identify basic problems. Then we created and integrated new graph metric in two created by us program modules for relevant knowledge aggregation from UMLS.
临床搜索引擎的开发是医学信息学的一个实际任务。该领域的主要问题是实现高质量的非结构化文本处理。本体论跨学科元词表 UMLS 可用于解决此问题。目前,还没有从 UMLS 中相关信息聚合的统一方法。在这项研究中,我们将 UMLS 表示为图形模型,并对 UMLS 结构进行了抽查,以确定基本问题。然后,我们在我们创建的两个程序模块中创建并集成了新的图形度量,用于从 UMLS 中聚合相关知识。