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Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis

BACKGROUND: The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) provides a valuable data source for post-vaccination adverse event analyses. The structured data in the system has been widely used, but the information in the write-up narratives is rarely included in these kinds of analyse...

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Detalles Bibliográficos
Autores principales: Tao, Cui, He, Yongqun, Yang, Hannah, Poland, Gregory A, Chute, Christopher G
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3554604/
https://www.ncbi.nlm.nih.gov/pubmed/23256916
http://dx.doi.org/10.1186/2041-1480-3-13
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author Tao, Cui
He, Yongqun
Yang, Hannah
Poland, Gregory A
Chute, Christopher G
author_facet Tao, Cui
He, Yongqun
Yang, Hannah
Poland, Gregory A
Chute, Christopher G
author_sort Tao, Cui
collection PubMed
description BACKGROUND: The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) provides a valuable data source for post-vaccination adverse event analyses. The structured data in the system has been widely used, but the information in the write-up narratives is rarely included in these kinds of analyses. In fact, the unstructured nature of the narratives makes the data embedded in them difficult to be used for any further studies. RESULTS: We developed an ontology-based approach to represent the data in the narratives in a “machine-understandable” way, so that it can be easily queried and further analyzed. Our focus is the time aspect in the data for time trending analysis. The Time Event Ontology (TEO), Ontology of Adverse Events (OAE), and Vaccine Ontology (VO) are leveraged for the semantic representation of this purpose. A VAERS case report is presented as a use case for the ontological representations. The advantages of using our ontology-based Semantic web representation and data analysis are emphasized. CONCLUSIONS: We believe that representing both the structured data and the data from write-up narratives in an integrated, unified, and “machine-understandable” way can improve research for vaccine safety analyses, causality assessments, and retrospective studies.
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spelling pubmed-35546042013-01-29 Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis Tao, Cui He, Yongqun Yang, Hannah Poland, Gregory A Chute, Christopher G J Biomed Semantics Research BACKGROUND: The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS) provides a valuable data source for post-vaccination adverse event analyses. The structured data in the system has been widely used, but the information in the write-up narratives is rarely included in these kinds of analyses. In fact, the unstructured nature of the narratives makes the data embedded in them difficult to be used for any further studies. RESULTS: We developed an ontology-based approach to represent the data in the narratives in a “machine-understandable” way, so that it can be easily queried and further analyzed. Our focus is the time aspect in the data for time trending analysis. The Time Event Ontology (TEO), Ontology of Adverse Events (OAE), and Vaccine Ontology (VO) are leveraged for the semantic representation of this purpose. A VAERS case report is presented as a use case for the ontological representations. The advantages of using our ontology-based Semantic web representation and data analysis are emphasized. CONCLUSIONS: We believe that representing both the structured data and the data from write-up narratives in an integrated, unified, and “machine-understandable” way can improve research for vaccine safety analyses, causality assessments, and retrospective studies. BioMed Central 2012-12-20 /pmc/articles/PMC3554604/ /pubmed/23256916 http://dx.doi.org/10.1186/2041-1480-3-13 Text en Copyright ©2012 Tao et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Tao, Cui
He, Yongqun
Yang, Hannah
Poland, Gregory A
Chute, Christopher G
Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis
title Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis
title_full Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis
title_fullStr Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis
title_full_unstemmed Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis
title_short Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis
title_sort ontology-based time information representation of vaccine adverse events in vaers for temporal analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3554604/
https://www.ncbi.nlm.nih.gov/pubmed/23256916
http://dx.doi.org/10.1186/2041-1480-3-13
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