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- Title
STO: Stroke Ontology for Accelerating Translational Stroke Research.
- Authors
Habibi-koolaee, Mahdi; Shahmoradi, Leila; Niakan Kalhori, Sharareh R.; Ghannadan, Hossein; Younesi, Erfan
- Abstract
Introduction: Ontology-based annotation of evidence, using disease-specific ontologies, can accelerate analysis and interpretation of the knowledge domain of diseases. Although many domain-specific disease ontologies have been developed so far, in the area of cardiovascular diseases, there is a lack of ontological representation of the disease knowledge domain of stroke. Methods: The stroke ontology (STO) was created on the basis of the ontology development life cycle and was built using Protégé ontology editor in the ontology web language format. The ontology was evaluated in terms of structural and functional features, expert evaluation, and competency questions. Results: The stroke ontology covers a broad range of major biomedical and risk factor concepts. The majority of concepts are enriched by synonyms, definitions, and references. The ontology attempts to incorporate different users' views on the stroke domain such as neuroscientists, molecular biologists, and clinicians. Evaluation of the ontology based on natural language processing showed a high precision (0.94), recall (0.80), and F-score (0.78) values, indicating that STO has an acceptable coverage of the stroke knowledge domain. Performance evaluation using competency questions designed by a clinician showed that the ontology can be used to answer expert questions in light of published evidence. Conclusions: The stroke ontology is the first, multiple-view ontology in the domain of brain stroke that can be used as a tool for representation, formalization, and standardization of the heterogeneous data related to the stroke domain. Since this is a draft version of the ontology, the contribution of the stroke scientific community can help to improve the usability of the current version.
- Subjects
TRANSLATIONAL research; ONTOLOGIES (Information retrieval); NATURAL language processing; MOLECULAR biologists; COMPETENCY assessment (Law)
- Publication
Neurology & Therapy, 2021, Vol 10, Issue 1, p321
- ISSN
2193-8253
- Publication type
Article
- DOI
10.1007/s40120-021-00248-1