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      KCI등재 SCOPUS

      Ontology for Symptomatic Treatment of Multiple Sclerosis

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      https://www.riss.kr/link?id=A108335077

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      다국어 초록 (Multilingual Abstract)

      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.
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      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 t...

      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.

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      참고문헌 (Reference)

      1 Pak J, "Workshop on e-business" Springer 10-18, 2009

      2 Dissanayake PI, "Using clinical reasoning ontologies to make smarter clinical decision support systems : a systematic review and data synthesis" 27 (27): 159-174, 2020

      3 Hadzic M, "Towards the mental health ontology" 284-288, 2008

      4 Miller P, "The pharmacological and nonpharmacological interventions for the management of fatigue related multiple sclerosis" 381 : 41-54, 2017

      5 Jensen M, "The neurological disease ontology" 4 (4): 42-, 2013

      6 Rommer PS, "Symptomatology and symptomatic treatment in multiple sclerosis : results from a nationwide MS registry" 25 (25): 1641-1652, 2019

      7 de Sa JC, "Symptomatic therapy in multiple sclerosis : a review for a multimodal approach in clinical practice" 4 (4): 139-168, 2011

      8 Shen Y, "Smart computing and communication" Springer 278-288, 2017

      9 Obrst L, "Semantic web" Springer 139-158, 2007

      10 Sirin E, "Pellet : a practical OWL-DL reasoner" 5 (5): 51-53, 2007

      1 Pak J, "Workshop on e-business" Springer 10-18, 2009

      2 Dissanayake PI, "Using clinical reasoning ontologies to make smarter clinical decision support systems : a systematic review and data synthesis" 27 (27): 159-174, 2020

      3 Hadzic M, "Towards the mental health ontology" 284-288, 2008

      4 Miller P, "The pharmacological and nonpharmacological interventions for the management of fatigue related multiple sclerosis" 381 : 41-54, 2017

      5 Jensen M, "The neurological disease ontology" 4 (4): 42-, 2013

      6 Rommer PS, "Symptomatology and symptomatic treatment in multiple sclerosis : results from a nationwide MS registry" 25 (25): 1641-1652, 2019

      7 de Sa JC, "Symptomatic therapy in multiple sclerosis : a review for a multimodal approach in clinical practice" 4 (4): 139-168, 2011

      8 Shen Y, "Smart computing and communication" Springer 278-288, 2017

      9 Obrst L, "Semantic web" Springer 139-158, 2007

      10 Sirin E, "Pellet : a practical OWL-DL reasoner" 5 (5): 51-53, 2007

      11 Maedche A, "Ontology learning for the semantic web" 16 (16): 72-79, 2001

      12 Noy NF, "Ontology development 101:a guide to creating your first ontology"

      13 Motik B, "OWL 2 web ontology language : structural specification and functional-style syntax" 27 (27): 159-, 2009

      14 Linker RA, "Navigating choice in multiple sclerosis management" 1 : 5-, 2019

      15 US Food and Drug Administration, "Medication Guides" Food and Drug Administration

      16 Malhotra A, "Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology" 10 (10): e0116718-, 2015

      17 Schulz S, "Guideline on developing good ontologies in the biomedical domain with description logics" Universitat Rostock

      18 Elmhadhbi L, "Enterprise interoperability VIII" Springer 131-140, 2019

      19 Willems LM, "Effectiveness of nonpharmacologic interventions in systemic sclerosis : a systematic review" 67 (67): 1426-1439, 2015

      20 Zhang Z, "Developing an ontology for representing the domain knowledge specific to non-pharmacological treatment for agitation in dementia" 6 (6): e12061-, 2020

      21 El-Sappagh S, "DMTO : a realistic ontology for standard diabetes mellitus treatment" 9 (9): 8-, 2018

      22 El-Sappagh S, "DDO : a diabetes mellitus diagnosis ontology" 3 : 5-, 2016

      23 Ng P, "Clinical decision-making in multiple sclerosis : challenges reported internationally with emerging treatment complexity" 4 (4): 320-328, 2015

      24 Arp R, "Building ontologies with basic formal ontology" MIT Press 2015

      25 Dostal M, "Automatic keyphrase extraction based on NLP and statistical method" 2011

      26 Browne P, "Atlas of Multiple Sclerosis 2013 : a growing global problem with widespread inequity" 83 (83): 1022-1024, 2014

      27 Amith M, "Assessing the practice of biomedical ontology evaluation : gaps and opportunities" 80 : 1-13, 2018

      28 Jensen M, "An ontological representation and analysis of patient-reported and clinical outcomes for multiple sclerosis" 2014-2018, 2014

      29 Daltrozzo T, "A systematic assessment of prevalence, incidence and regional distribution of multiple sclerosis in Bavaria from 2006 to 2015" 9 : 871-, 2018

      30 Raad J, "A survey on ontology evaluation methods" 179-186, 2015

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