TY - JOUR
T1 - Developing an intuitive graph representation of knowledge for nonpharmacological treatment of psychotic symptoms in dementia
AU - Zhang, Zhenyu
AU - Yu, Ping
AU - Pai, Nagesh
AU - Chang, Hui Chen (Rita)
AU - Chen, Shiyan
AU - Yin, Mengyang
AU - Song, Ting
AU - Lau, Sim Kim
AU - Deng, Chao
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - https://hdl.handle.net/1959.7/uws:69496
UR - https://www.proquest.com/docview/2643989171/fulltextPDF/6DD1BD43208446BEPQ/1?accountid=36155
U2 - 10.3928/00989134-20220308-02
DO - 10.3928/00989134-20220308-02
M3 - Article
SN - 0098-9134
VL - 48
SP - 49
EP - 55
JO - Journal of Gerontological Nursing
JF - Journal of Gerontological Nursing
IS - 4
ER -