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. 2013 Mar 18:2013:149-53.
eCollection 2013.

An information extraction framework for cohort identification using electronic health records

Hongfang Liu  1 , Suzette J Bielinski, Sunghwan Sohn, Sean Murphy, Kavishwar B Wagholikar, Siddhartha R Jonnalagadda, K E Ravikumar, Stephen T Wu, Iftikhar J Kullo, Christopher G Chute
Affiliations

An information extraction framework for cohort identification using electronic health records

Hongfang Liu et al. AMIA Jt Summits Transl Sci Proc. .

Abstract

Information extraction (IE), a natural language processing (NLP) task that automatically extracts structured or semi-structured information from free text, has become popular in the clinical domain for supporting automated systems at point-of-care and enabling secondary use of electronic health records (EHRs) for clinical and translational research. However, a high performance IE system can be very challenging to construct due to the complexity and dynamic nature of human language. In this paper, we report an IE framework for cohort identification using EHRs that is a knowledge-driven framework developed under the Unstructured Information Management Architecture (UIMA). A system to extract specific information can be developed by subject matter experts through expert knowledge engineering of the externalized knowledge resources used in the framework.

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Figures

Figure 1.
Figure 1.
System architecture of the IE framework under cTAKES.
See this image and copyright information in PMC

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