SNOMED reaching its adolescence: Ontologists’ and logicians’ health check

Schulz, Stefan; Suntisrivaraporn, Boontawee; Baader, Franz; Boeker, Martin

doi:10.1016/j.ijmedinf.2008.06.004

Cited by 74 publications

(37 citation statements)

References 19 publications

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“…26 Roadmaps for overall improvement of SNOMED-CTr by addressing both logical and ontological issues are also being considered. 27,28 Although the primary purpose of adding these axioms is to automatically identify inconsistencies and misannotations in the ontologies, they can also have an important role for enhancing the way conceptual similarity is calculated. 29 Therefore, the inclusion of the description logical axioms being added to biomedical ontologies in similarity measures is much required.…”

Section: Biomedical Ontologiesmentioning

confidence: 99%

The Next Generation of Similarity Measures That Fully Explore the Semantics in Biomedical Ontologies

Couto

Pinto

2013

J. Bioinform. Comput. Biol.

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There is a prominent trend to augment and improve the formality of biomedical ontologies. For example, this is shown by the current e®ort on adding description logic axioms, such as disjointness. One of the key ontology applications that can take advantage of this e®ort is the conceptual (functional) similarity measurement. The presence of description logic axioms in biomedical ontologies make the current structural or extensional approaches weaker and further away from providing sound semantics-based similarity measures. Although bene¯cial in small ontologies, the exploration of description logic axioms by semantics-based similarity measures is computational expensive. This limitation is critical for biomedical ontologies that normally contain thousands of concepts. Thus in the process of gaining their rightful place, biomedical functional similarity measures have to take the journey of¯nding how this rich and powerful knowledge can be fully explored while keeping feasible computational costs. This manuscript aims at promoting and guiding the development of compelling tools that deliver what the biomedical community will require in a near future: a next-generation of biomedical similarity measures that e±ciently and fully explore the semantics present in biomedical ontologies.

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Section: Biomedical Ontologiesmentioning

confidence: 99%

The Next Generation of Similarity Measures That Fully Explore the Semantics in Biomedical Ontologies

Couto

Pinto

2013

J. Bioinform. Comput. Biol.

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“…Semantic, structural, and ontological techniques are offered by Rector et al 25,26 who identified major types of errors in SCT that were caused by problems in Description Logic modeling or in concept classification. Schulz et al [27][28][29] analyzed SCT's 'health' from an ontological and logical perspective, identifying major problem areas.…”

Section: Introductionmentioning

confidence: 99%

Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies

Ochs

Geller

Perl

et al. 2015

Journal of the American Medical Informatics Association

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“…[10]. Therefore, most authors still rely on EL++ [11,12] when performing semantic queries on large ontologies. This article presents our new strategy for building the OntoADR resource.…”

Section: Inmentioning

confidence: 99%

OntoADR a semantic resource describing adverse drug reactions to support searching, coding, and information retrieval

Souvignet

Declerck

Asfari

et al. 2016

Journal of Biomedical Informatics

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The methods we describe in this article could be adapted and extended to other terminologies which do not benefit from a formal semantic representation, thus enabling better data retrieval performance. Our custom groupings of MedDRA terms were used while performing signal detection, which suggests that the graphical user interface we are currently implementing to process OntoADR could be usefully integrated into specialized pharmacovigilance software that rely on MedDRA.

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SNOMED reaching its adolescence: Ontologists’ and logicians’ health check

Cited by 74 publications

References 19 publications

The Next Generation of Similarity Measures That Fully Explore the Semantics in Biomedical Ontologies

The Next Generation of Similarity Measures That Fully Explore the Semantics in Biomedical Ontologies

Scalable quality assurance for large SNOMED CT hierarchies using subject-based subtaxonomies

OntoADR a semantic resource describing adverse drug reactions to support searching, coding, and information retrieval

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