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Ontology for Symptomatic Treatment of Multiple Sclerosis
OBJECTIVES: Symptomatic treatment is an essential component in the overall treatment of multiple sclerosis (MS). However, knowledge in this regard is confusing and scattered. Physicians also have challenges in choosing symptomatic treatment based on the patient’s condition. To share, update, and reu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Society of Medical Informatics
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9672491/ https://www.ncbi.nlm.nih.gov/pubmed/36380430 http://dx.doi.org/10.4258/hir.2022.28.4.332 |
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author | Esfahani, Misagh Zahiri Ahmadi, Maryam Adibi, Iman |
author_facet | Esfahani, Misagh Zahiri Ahmadi, Maryam Adibi, Iman |
author_sort | Esfahani, Misagh Zahiri |
collection | PubMed |
description | OBJECTIVES: Symptomatic treatment is an essential component in the overall treatment of multiple sclerosis (MS). However, knowledge in this regard is confusing and scattered. Physicians also have challenges in choosing symptomatic treatment based on the patient’s condition. To share, update, and reuse this knowledge, the aim of this study was to provide an ontology for MS symptomatic treatment. METHODS: The Symptomatic Treatment of Multiple Sclerosis Ontology (STMSO) was developed according to Ontology Development 101 and a guideline for developing good ontologies in the biomedical domain. We obtained knowledge and rules through a systematic review and entered this knowledge in the form of classes and subclasses in the ontology. We then mapped the ontology using the Basic Formal Ontology (BFO) and Ontology for General Medical Sciences (OGMS) as reference ontologies. The ontology was built using Protégé Editor in the Web Ontology Language format. Finally, an evaluation was done by experts using criterion-based approaches in terms of accuracy, clarity, consistency, and completeness. RESULTS: The knowledge extraction phase identified 110 articles related to the ontology in the form of 626 classes, 40 object properties, and 139 rules. Five general classes included “patient,” “symptoms,” “pharmacological treatment,” “treatment plan,” and “measurement index.” The evaluation in terms of standards for biomedical ontology showed that STMSO was accurate, clear, consistent, and complete. CONCLUSIONS: STMSO is the first comprehensive semantic representation of the symptomatic treatment of MS and provides a major step toward the development of intelligent clinical decision support systems for symptomatic MS treatment. |
format | Online Article Text |
id | pubmed-9672491 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Korean Society of Medical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-96724912022-11-29 Ontology for Symptomatic Treatment of Multiple Sclerosis Esfahani, Misagh Zahiri Ahmadi, Maryam Adibi, Iman Healthc Inform Res Original Article OBJECTIVES: Symptomatic treatment is an essential component in the overall treatment of multiple sclerosis (MS). However, knowledge in this regard is confusing and scattered. Physicians also have challenges in choosing symptomatic treatment based on the patient’s condition. To share, update, and reuse this knowledge, the aim of this study was to provide an ontology for MS symptomatic treatment. METHODS: The Symptomatic Treatment of Multiple Sclerosis Ontology (STMSO) was developed according to Ontology Development 101 and a guideline for developing good ontologies in the biomedical domain. We obtained knowledge and rules through a systematic review and entered this knowledge in the form of classes and subclasses in the ontology. We then mapped the ontology using the Basic Formal Ontology (BFO) and Ontology for General Medical Sciences (OGMS) as reference ontologies. The ontology was built using Protégé Editor in the Web Ontology Language format. Finally, an evaluation was done by experts using criterion-based approaches in terms of accuracy, clarity, consistency, and completeness. RESULTS: The knowledge extraction phase identified 110 articles related to the ontology in the form of 626 classes, 40 object properties, and 139 rules. Five general classes included “patient,” “symptoms,” “pharmacological treatment,” “treatment plan,” and “measurement index.” The evaluation in terms of standards for biomedical ontology showed that STMSO was accurate, clear, consistent, and complete. CONCLUSIONS: STMSO is the first comprehensive semantic representation of the symptomatic treatment of MS and provides a major step toward the development of intelligent clinical decision support systems for symptomatic MS treatment. Korean Society of Medical Informatics 2022-10 2022-10-31 /pmc/articles/PMC9672491/ /pubmed/36380430 http://dx.doi.org/10.4258/hir.2022.28.4.332 Text en © 2022 The Korean Society of Medical Informatics https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Esfahani, Misagh Zahiri Ahmadi, Maryam Adibi, Iman Ontology for Symptomatic Treatment of Multiple Sclerosis |
title | Ontology for Symptomatic Treatment of Multiple Sclerosis |
title_full | Ontology for Symptomatic Treatment of Multiple Sclerosis |
title_fullStr | Ontology for Symptomatic Treatment of Multiple Sclerosis |
title_full_unstemmed | Ontology for Symptomatic Treatment of Multiple Sclerosis |
title_short | Ontology for Symptomatic Treatment of Multiple Sclerosis |
title_sort | ontology for symptomatic treatment of multiple sclerosis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9672491/ https://www.ncbi.nlm.nih.gov/pubmed/36380430 http://dx.doi.org/10.4258/hir.2022.28.4.332 |
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