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Developing an intuitive graph representation of knowledge for nonpharmacological treatment of psychotic symptoms in dementia

  • Zhenyu Zhang
  • , Ping Yu
  • , Nagesh Pai
  • , Hui Chen (Rita) Chang
  • , Shiyan Chen
  • , Mengyang Yin
  • , Ting Song
  • , Sim Kim Lau
  • , Chao Deng

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Applying person-centered, nonpharmacological interventions to manage psychotic symptoms of dementia is promoted for health care professionals, particularly gerontological nurses, who are responsible for care of older adults in nursing homes. A knowledge graph is a graph consisting of a set of concepts that are linked together by their interrelationship and has been widely used as a formal representation of domain knowledge in health. However, there is lack of a knowledge graph for nonpharmacological treatment of psychotic symptoms in dementia. Therefore, we developed a comprehensive, human- and machine-understandable knowledge graph for this domain, named Dementia-Related Psychotic Symptom Nonpharmacological Treatment Ontology (DRPSNPTO). This graph was built by adopting the established NeOn methodology, a knowledge graph engineering method, to meet the quality standards for biomedical knowledge graphs. This intuitive graph representation of the domain knowledge sets a new direction for visualizing and computerizing gerontological knowledge to facilitate human comprehension and build intelligent aged care information systems.
Original languageEnglish
Pages (from-to)49-55
Number of pages7
JournalJournal of Gerontological Nursing
Volume48
Issue number4
DOIs
Publication statusPublished - Apr 2022

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