Identifying Breast Cancer Concepts in SNOMED-CT Using Large Text Corpus

Zharko Aleksovski; Merlijn Sevenster

Electronic Healthcare. Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers

Research Article

Identifying Breast Cancer Concepts in SNOMED-CT Using Large Text Corpus

Download

588 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-642-23635-8_4,
    author={Zharko Aleksovski and Merlijn Sevenster},
    title={Identifying Breast Cancer Concepts in SNOMED-CT Using Large Text Corpus},
    proceedings={Electronic Healthcare. Third International Conference, eHealth 2010, Casablanca, Morocco, December 13-15, 2010, Revised Selected Papers},
    proceedings_a={E-HEALTH},
    year={2012},
    month={10},
    keywords={ontology SNOMED-CT breast cancer term frequency},
    doi={10.1007/978-3-642-23635-8_4}
}

Zharko Aleksovski
Merlijn Sevenster
Year: 2012
Identifying Breast Cancer Concepts in SNOMED-CT Using Large Text Corpus
E-HEALTH
Springer
DOI: 10.1007/978-3-642-23635-8_4

Zharko Aleksovski¹^,*, Merlijn Sevenster¹

1: Philips Research Europe

*Contact email: zharko.aleksovski@philips.com

Abstract

Large medical ontologies can be of great help in building a specialized clinical information system. First step in their use is to identify the subset of concepts which are relevant to the specialty. In this paper we present a method to automatically identify the breast cancer concepts from the ontology using large text corpus as source of knowledge. In addition to finding them, the concepts are also assigned relevance values.

Keywords: ontology SNOMED-CT breast cancer term frequency

Published: 2012-10-17

: http://dx.doi.org/10.1007/978-3-642-23635-8_4

Identifying Breast Cancer Concepts in SNOMED-CT Using Large Text Corpus

Abstract

About EAI

Community

Publish with EAI