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Review
. 2015 Dec;58 Suppl(Suppl):S67-S77.
doi: 10.1016/j.jbi.2015.07.001. Epub 2015 Jul 22.

Identifying risk factors for heart disease over time: Overview of 2014 i2b2/UTHealth shared task Track 2

Affiliations
Review

Identifying risk factors for heart disease over time: Overview of 2014 i2b2/UTHealth shared task Track 2

Amber Stubbs et al. J Biomed Inform. 2015 Dec.

Abstract

The second track of the 2014 i2b2/UTHealth natural language processing shared task focused on identifying medical risk factors related to Coronary Artery Disease (CAD) in the narratives of longitudinal medical records of diabetic patients. The risk factors included hypertension, hyperlipidemia, obesity, smoking status, and family history, as well as diabetes and CAD, and indicators that suggest the presence of those diseases. In addition to identifying the risk factors, this track of the 2014 i2b2/UTHealth shared task studied the presence and progression of the risk factors in longitudinal medical records. Twenty teams participated in this track, and submitted 49 system runs for evaluation. Six of the top 10 teams achieved F1 scores over 0.90, and all 10 scored over 0.87. The most successful system used a combination of additional annotations, external lexicons, hand-written rules and Support Vector Machines. The results of this track indicate that identification of risk factors and their progression over time is well within the reach of automated systems.

Keywords: CAD; Clinical narratives; Diabetes; Natural language processing.

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Conflict of interest statement

Conflict of Interest Statement

June 18, 2015

To whom it may concern,

This statement affirms that Amber Stubbs, Christopher Kotfila, Hua Xu, and Ozlem Uzuner, the authors of the paper “Identifying risk factors for heart disease over time: Overview of 2014 i2b2/UTHealth shared task Track 2” do not have any conflicts of interest relating to this paper or its results.

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