ArticleAlzheimer's & dementia (New York, N. Y.)2020
Developing an ontology for representing the domain knowledge specific to non-pharmacological treatment for agitation in dementia.
Article in Alzheimer's & dementia (New York, N. Y.), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.
- Prevalence of Antibiotic Resistance in Older Adults and Alzheimer's Disease Patients: A Systematic Review and Meta-Analysis.Journal of Alzheimer's disease reports · 2024Pooled it
- eDEM-CONNECT: agitation ontology for the intelligent support of informal caregivers of people with dementia.Frontiers in aging · 2026Article
- An Ontology-Based Approach for Understanding Appendicectomy Processes and Associated Resources.Healthcare (Basel, Switzerland) · 2024Article
- Developing an ontology of non-pharmacological treatment for emotional and mood disturbances in dementia.Scientific reports · 2024Article
- Ontological Model in the Identification of Emotional Aspects in Alzheimer Patients.Healthcare (Basel, Switzerland) · 2023Article
- Ontology for Symptomatic Treatment of Multiple Sclerosis.Healthcare informatics research · 2022Article
- Developing an ontology for representing the domain knowledge specific to non-pharmacological treatment for agitation in dementia.Alzheimer's & dementia (New York, N. Y.) · 2020Article
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Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionA large volume of clinical care data has been generated for managing agitation in dementia. However, the valuable information in these data has not been used effectively to generate insights for improving the quality of care. Application of artificial intelligence technologies offers us enormous opportunities to reuse these data. For health data science to achieve this, this study focuses on using ontology to coding clinical knowledge for non-pharmacological treatment of agitation in a machine-readable format.
methodsThe resultant ontology-Dementia-Related Agitation Non-Pharmacological Treatment Ontology (DRANPTO)-was developed using a method adopted from the NeOn methodology.
resultsDRANPTO consisted of 569 concepts and 48 object properties. It meets the standards for biomedical ontology. DISCUSSION: DRANPTO is the first comprehensive semantic representation of non-pharmacological management for agitation in dementia in the long-term care setting. As a knowledge base, it will play a vital role to facilitate the development of intelligent systems for managing agitation in dementia.
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