Using chief complaints for syndromic surveillance: A review of chief complaint based classifiers in North America

被引:35
作者
Conway, Mike [1 ]
Dowling, John N. [2 ]
Chapman, Wendy W. [1 ]
机构
[1] Univ Calif San Diego, Div Biomed Informat, La Jolla, CA 92093 USA
[2] Univ Pittsburgh, Dept Biomed Informat, Pittsburgh, PA 15260 USA
关键词
Chief complaints; Syndromic surveillance; Natural language processing; Medical language processing; PUBLIC-HEALTH; BIOTERRORISM; SYSTEM; CLASSIFICATION; PROJECT; RODS;
D O I
10.1016/j.jbi.2013.04.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A major goal of Natural Language Processing in the public health informatics domain is the automatic extraction and encoding of data stored in free text patient records. This extracted data can then be utilized by computerized systems to perform syndromic surveillance. In particular, the chief complaint-a short string that describes a patient's symptoms-has come to be a vital resource for syndromic surveillance in the North American context due to its near ubiquity. This paper reviews fifteen systems in North America-at the city, county, state and federal level-that use chief complaints for syndromic surveillance. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:734 / 743
页数:10
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