Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000

K. Milian; Z. Aleksovski; R. Vdovjak; A.C.M. ten Teije; F.A.H. van Harmelen

doi:10.1007/978-3-642-11808-1_5

Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000

K. Milian
, Z. Aleksovski
, R. Vdovjak
, A.C.M. ten Teije
, F.A.H. van Harmelen

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

Modern medical vocabularies can contain up to hundreds of thousands of concepts. In any particular use-case only a small fraction of these will be needed. In this paper we first define two notions of a disease-centric subdomain of a large ontology. We then explore two methods for identifying disease-centric subdomains of such large medical vocabularies. The first method is based on lexically querying the ontology with an iteratively extended set of seed queries. The second method is based on manual mapping between concepts from a medical guideline document and ontology concepts. Both methods include concept-expansion over subsumption and equality relations. We use both methods to determine a breast-cancer-centric subdomain of the SNOMED CT ontology. Our experiments show that the two methods produce a considerable overlap, but they also yield a large degree of complementarity, with interesting differences between the sets of concepts that they return. Analysis of the results reveals strengths and weaknesses of the different methods.

Original language	English
Title of host publication	Knowledge Representation for Health-Care: Data, Processes and Guidelines, AIME 2009, Workshop KR4HC 2009, Revised Selected and Invited Papers
Editors	D. Riano, A.C.M. ten Teije, S. Miksch, M. Peleg
Place of Publication	Verona, Italy
Pages	50-63
Number of pages	14
DOIs	https://doi.org/10.1007/978-3-642-11808-1_5
Publication status	Published - 2010
Event	Workshop on Knowledge Representation for Health-Care: Data, Processes and Guidelines, KR4HC 2009. Held in Conjunction with the 12th Conference on Artificial Intelligence in Medicine, AIME 2009 - Verona, Italy Duration: 19 Jul 2009 → 19 Jul 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5943 LNAI
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	Workshop on Knowledge Representation for Health-Care: Data, Processes and Guidelines, KR4HC 2009. Held in Conjunction with the 12th Conference on Artificial Intelligence in Medicine, AIME 2009
Country/Territory	Italy
City	Verona
Period	19/07/09 → 19/07/09

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Disease related concepts
Identifying ontology subdomain
Mapping medical terminologies
Medical guidelines
Ontology subsetting
Seed queries

Access to Document

10.1007/978-3-642-11808-1_5

KR4HC09-bookversion-2011Submitted manuscript, 216 KB

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Milian, K., Aleksovski, Z., Vdovjak, R., ten Teije, A. C. M., & van Harmelen, F. A. H. (2010). Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000. In D. Riano, A. C. M. ten Teije, S. Miksch, & M. Peleg (Eds.), Knowledge Representation for Health-Care: Data, Processes and Guidelines, AIME 2009, Workshop KR4HC 2009, Revised Selected and Invited Papers (pp. 50-63). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5943 LNAI).. https://doi.org/10.1007/978-3-642-11808-1_5

Milian, K. ; Aleksovski, Z. ; Vdovjak, R. et al. / Identifying disease-centric subdomains in very large medical ontologies : A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000. Knowledge Representation for Health-Care: Data, Processes and Guidelines, AIME 2009, Workshop KR4HC 2009, Revised Selected and Invited Papers. editor / D. Riano ; A.C.M. ten Teije ; S. Miksch ; M. Peleg. Verona, Italy, 2010. pp. 50-63 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000",

abstract = "Modern medical vocabularies can contain up to hundreds of thousands of concepts. In any particular use-case only a small fraction of these will be needed. In this paper we first define two notions of a disease-centric subdomain of a large ontology. We then explore two methods for identifying disease-centric subdomains of such large medical vocabularies. The first method is based on lexically querying the ontology with an iteratively extended set of seed queries. The second method is based on manual mapping between concepts from a medical guideline document and ontology concepts. Both methods include concept-expansion over subsumption and equality relations. We use both methods to determine a breast-cancer-centric subdomain of the SNOMED CT ontology. Our experiments show that the two methods produce a considerable overlap, but they also yield a large degree of complementarity, with interesting differences between the sets of concepts that they return. Analysis of the results reveals strengths and weaknesses of the different methods.",

keywords = "Disease related concepts, Identifying ontology subdomain, Mapping medical terminologies, Medical guidelines, Ontology subsetting, Seed queries",

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year = "2010",

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booktitle = "Knowledge Representation for Health-Care: Data, Processes and Guidelines, AIME 2009, Workshop KR4HC 2009, Revised Selected and Invited Papers",

note = "Workshop on Knowledge Representation for Health-Care: Data, Processes and Guidelines, KR4HC 2009. Held in Conjunction with the 12th Conference on Artificial Intelligence in Medicine, AIME 2009 ; Conference date: 19-07-2009 Through 19-07-2009",

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Milian, K, Aleksovski, Z, Vdovjak, R, ten Teije, ACM & van Harmelen, FAH 2010, Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000. in D Riano, ACM ten Teije, S Miksch & M Peleg (eds), Knowledge Representation for Health-Care: Data, Processes and Guidelines, AIME 2009, Workshop KR4HC 2009, Revised Selected and Invited Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5943 LNAI, Verona, Italy, pp. 50-63, Workshop on Knowledge Representation for Health-Care: Data, Processes and Guidelines, KR4HC 2009. Held in Conjunction with the 12th Conference on Artificial Intelligence in Medicine, AIME 2009, Verona, Italy, 19/07/09. https://doi.org/10.1007/978-3-642-11808-1_5

Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000. / Milian, K.; Aleksovski, Z.; Vdovjak, R. et al.
Knowledge Representation for Health-Care: Data, Processes and Guidelines, AIME 2009, Workshop KR4HC 2009, Revised Selected and Invited Papers. ed. / D. Riano; A.C.M. ten Teije; S. Miksch; M. Peleg. Verona, Italy, 2010. p. 50-63 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5943 LNAI).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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KW - Medical guidelines

KW - Ontology subsetting

KW - Seed queries

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Milian K, Aleksovski Z, Vdovjak R, ten Teije ACM , van Harmelen FAH. Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000. In Riano D, ten Teije ACM, Miksch S, Peleg M, editors, Knowledge Representation for Health-Care: Data, Processes and Guidelines, AIME 2009, Workshop KR4HC 2009, Revised Selected and Invited Papers. Verona, Italy. 2010. p. 50-63. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-11808-1_5

Identifying disease-centric subdomains in very large medical ontologies: A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Persistent URL (handle)

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Cite this