Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Esfahani, Misagh Zahiri, Ahmadi, Maryam, Adibi, Iman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Medical Informatics 2022
Materias:
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
_version_ 1784832747086282752
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
work_keys_str_mv AT esfahanimisaghzahiri ontologyforsymptomatictreatmentofmultiplesclerosis
AT ahmadimaryam ontologyforsymptomatictreatmentofmultiplesclerosis
AT adibiiman ontologyforsymptomatictreatmentofmultiplesclerosis