| Literature DB >> 32175080 |
Xin Li1, Haoyang Liu2, Xu Zhao3, Guigang Zhang4, Chunxiao Xing5.
Abstract
In this study, a medical knowledge graph is constructed from the electronic medical record text of knee osteoarthritis patients to support intelligent medical applications such as knowledge retrieval and decision support, and to promote the sharing of medical resources. After constructing the domain ontology of knee osteoarthritis and manually labeling, we trained a machine learning model to automatically perform entity recognition and entity relation extraction, and then used a graph database to construct the knowledge graph of knee osteoarthritis. The experiment proves that the knowledge graph is comprehensive and reliable, and the knowledge graph construction method proposed in this study is effective. © Springer Nature Switzerland AG 2020.Entities:
Keywords: Electronic medical record; Entity recognition; Entity relation extraction; Knee osteoarthritis; Knowledge graph
Year: 2020 PMID: 32175080 PMCID: PMC7046853 DOI: 10.1007/s13755-020-0102-4
Source DB: PubMed Journal: Health Inf Sci Syst ISSN: 2047-2501