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STO: Stroke Ontology for Accelerating Translational Stroke Research
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Healthcare
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140017/ https://www.ncbi.nlm.nih.gov/pubmed/33886080 http://dx.doi.org/10.1007/s40120-021-00248-1 |
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author | Habibi-koolaee, Mahdi Shahmoradi, Leila Niakan Kalhori, Sharareh R. Ghannadan, Hossein Younesi, Erfan |
author_facet | Habibi-koolaee, Mahdi Shahmoradi, Leila Niakan Kalhori, Sharareh R. Ghannadan, Hossein Younesi, Erfan |
author_sort | Habibi-koolaee, Mahdi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8140017 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Healthcare |
record_format | MEDLINE/PubMed |
spelling | pubmed-81400172021-06-03 STO: Stroke Ontology for Accelerating Translational Stroke Research Habibi-koolaee, Mahdi Shahmoradi, Leila Niakan Kalhori, Sharareh R. Ghannadan, Hossein Younesi, Erfan Neurol Ther Original Research 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. Springer Healthcare 2021-04-22 /pmc/articles/PMC8140017/ /pubmed/33886080 http://dx.doi.org/10.1007/s40120-021-00248-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc/4.0/Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Habibi-koolaee, Mahdi Shahmoradi, Leila Niakan Kalhori, Sharareh R. Ghannadan, Hossein Younesi, Erfan STO: Stroke Ontology for Accelerating Translational Stroke Research |
title | STO: Stroke Ontology for Accelerating Translational Stroke Research |
title_full | STO: Stroke Ontology for Accelerating Translational Stroke Research |
title_fullStr | STO: Stroke Ontology for Accelerating Translational Stroke Research |
title_full_unstemmed | STO: Stroke Ontology for Accelerating Translational Stroke Research |
title_short | STO: Stroke Ontology for Accelerating Translational Stroke Research |
title_sort | sto: stroke ontology for accelerating translational stroke research |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8140017/ https://www.ncbi.nlm.nih.gov/pubmed/33886080 http://dx.doi.org/10.1007/s40120-021-00248-1 |
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