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. 2012:2012:568-76.
Epub 2012 Nov 3.

Towards a semantic lexicon for clinical natural language processing

Hongfang Liu  1 , Stephen T Wu, Dingcheng Li, Siddhartha Jonnalagadda, Sunghwan Sohn, Kavishwar Wagholikar, Peter J Haug, Stanley M Huff, Christopher G Chute
Affiliations

Towards a semantic lexicon for clinical natural language processing

Hongfang Liu et al. AMIA Annu Symp Proc. 2012.

Abstract

A semantic lexicon which associates words and phrases in text to concepts is critical for extracting and encoding clinical information in free text and therefore achieving semantic interoperability between structured and unstructured data in Electronic Health Records (EHRs). Directly using existing standard terminologies may have limited coverage with respect to concepts and their corresponding mentions in text. In this paper, we analyze how tokens and phrases in a large corpus distribute and how well the UMLS captures the semantics. A corpus-driven semantic lexicon, MedLex, has been constructed where the semantics is based on the UMLS assisted with variants mined and usage information gathered from clinical text. The detailed corpus analysis of tokens, chunks, and concept mentions shows the UMLS is an invaluable source for natural language processing. Increasing the semantic coverage of tokens provides a good foundation in capturing clinical information comprehensively. The study also yields some insights in developing practical NLP systems.

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Figures

Figure 1.
Figure 1.
Histogram of different token groups.
Figure 2.
Figure 2.
Histogram of different token groups.
See this image and copyright information in PMC

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