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SNOMED CT standard ontology based on the ontology for general medical science
BACKGROUND: Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is a comprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic health data. Some efforts have been made to capture the contents of SCT as Web Onto...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6119323/ https://www.ncbi.nlm.nih.gov/pubmed/30170591 http://dx.doi.org/10.1186/s12911-018-0651-5 |
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author | El-Sappagh, Shaker Franda, Francesco Ali, Farman Kwak, Kyung-Sup |
author_facet | El-Sappagh, Shaker Franda, Francesco Ali, Farman Kwak, Kyung-Sup |
author_sort | El-Sappagh, Shaker |
collection | PubMed |
description | BACKGROUND: Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is a comprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic health data. Some efforts have been made to capture the contents of SCT as Web Ontology Language (OWL), but these efforts have been hampered by the size and complexity of SCT. METHOD: Our proposal here is to develop an upper-level ontology and to use it as the basis for defining the terms in SCT in a way that will support quality assurance of SCT, for example, by allowing consistency checks of definitions and the identification and elimination of redundancies in the SCT vocabulary. Our proposed upper-level SCT ontology (SCTO) is based on the Ontology for General Medical Science (OGMS). RESULTS: The SCTO is implemented in OWL 2, to support automatic inference and consistency checking. The approach will allow integration of SCT data with data annotated using Open Biomedical Ontologies (OBO) Foundry ontologies, since the use of OGMS will ensure consistency with the Basic Formal Ontology, which is the top-level ontology of the OBO Foundry. Currently, the SCTO contains 304 classes, 28 properties, 2400 axioms, and 1555 annotations. It is publicly available through the bioportal at http://bioportal.bioontology.org/ontologies/SCTO/. CONCLUSION: The resulting ontology can enhance the semantics of clinical decision support systems and semantic interoperability among distributed electronic health records. In addition, the populated ontology can be used for the automation of mobile health applications. |
format | Online Article Text |
id | pubmed-6119323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61193232018-09-05 SNOMED CT standard ontology based on the ontology for general medical science El-Sappagh, Shaker Franda, Francesco Ali, Farman Kwak, Kyung-Sup BMC Med Inform Decis Mak Research Article BACKGROUND: Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT, hereafter abbreviated SCT) is a comprehensive medical terminology used for standardizing the storage, retrieval, and exchange of electronic health data. Some efforts have been made to capture the contents of SCT as Web Ontology Language (OWL), but these efforts have been hampered by the size and complexity of SCT. METHOD: Our proposal here is to develop an upper-level ontology and to use it as the basis for defining the terms in SCT in a way that will support quality assurance of SCT, for example, by allowing consistency checks of definitions and the identification and elimination of redundancies in the SCT vocabulary. Our proposed upper-level SCT ontology (SCTO) is based on the Ontology for General Medical Science (OGMS). RESULTS: The SCTO is implemented in OWL 2, to support automatic inference and consistency checking. The approach will allow integration of SCT data with data annotated using Open Biomedical Ontologies (OBO) Foundry ontologies, since the use of OGMS will ensure consistency with the Basic Formal Ontology, which is the top-level ontology of the OBO Foundry. Currently, the SCTO contains 304 classes, 28 properties, 2400 axioms, and 1555 annotations. It is publicly available through the bioportal at http://bioportal.bioontology.org/ontologies/SCTO/. CONCLUSION: The resulting ontology can enhance the semantics of clinical decision support systems and semantic interoperability among distributed electronic health records. In addition, the populated ontology can be used for the automation of mobile health applications. BioMed Central 2018-08-31 /pmc/articles/PMC6119323/ /pubmed/30170591 http://dx.doi.org/10.1186/s12911-018-0651-5 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article El-Sappagh, Shaker Franda, Francesco Ali, Farman Kwak, Kyung-Sup SNOMED CT standard ontology based on the ontology for general medical science |
title | SNOMED CT standard ontology based on the ontology for general medical science |
title_full | SNOMED CT standard ontology based on the ontology for general medical science |
title_fullStr | SNOMED CT standard ontology based on the ontology for general medical science |
title_full_unstemmed | SNOMED CT standard ontology based on the ontology for general medical science |
title_short | SNOMED CT standard ontology based on the ontology for general medical science |
title_sort | snomed ct standard ontology based on the ontology for general medical science |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6119323/ https://www.ncbi.nlm.nih.gov/pubmed/30170591 http://dx.doi.org/10.1186/s12911-018-0651-5 |
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