StrokePEO: Construction of a Clinical Ontology for Physical Examination of Stroke

Zhanzhong Gu, Xiguang Yang, Wenjing Jia, Chengpei Xu, Ping Yu, Xiangjian He, Hongjie Chen, Yiguang Lin

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Clinical ontology is a standardized medical knowledge representation model that facilitates the integration and analysis of a large amount of heterogeneous electronic health record (EHR) data. Using ontologies to represent clinical terms can improve data integration to build robust and interoperable medical information systems. To date, there is no ontology existing to represent the medical knowledge for physical examination of stroke, which has inhibited the stroke physicians to make full use of clinical information captured in EHR data to understand stroke patient's health status and plan effective medication and rehabilitation treatment. In this research, we co-design with two stroke clinical specialists a stroke clinical ontology "StrokePEO"using advanced natural language processing and deep learning techniques to extract terms and their relationships from real clinical case records provided by a tertiary hospital in China. We apply the W3C Resource Description Framework (RDF) data model to represent these clinical terms and relationships, and successfully store all case data in a graph database with StrokePEO. Our experiment results suggest that our methods and the output of StrokePEO can be applied in various medical contexts that require extraction of medical knowledge from free text for decision making. These include, but not limited to, physical assessment, drug and rehabilitation treatment outcome evaluation, medication effect analysis, and patient risk prediction.

Original languageEnglish
Title of host publicationProceedings - 2022 9th International Conference on Digital Home, ICDH 2022
EditorsRuo-mei Wang, Zhong-xuan Luo, Bao-cai Yin, Jie-qing Tan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages218-223
Number of pages6
ISBN (Electronic)9781665454780
DOIs
Publication statusPublished - 2022
Event9th International Conference on Digital Home, ICDH 2022 - Guangzhou, China
Duration: 28 Oct 202230 Oct 2022

Publication series

NameProceedings - 2022 9th International Conference on Digital Home, ICDH 2022

Conference

Conference9th International Conference on Digital Home, ICDH 2022
Country/TerritoryChina
CityGuangzhou
Period28/10/2230/10/22

Keywords

  • Electronic health records
  • clinical ontology
  • physical examination
  • stroke
  • term relationship extraction

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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