Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm.
Document-level classification of CT pulmonary angiography reports based on an extension of the ConText algorithm.
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DOI:
10.1016/j.jbi.2011.03.011
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发表时间:
2011-10
影响因子:
4.5
通讯作者:
Chapman WW
中科院分区:
文献类型:
--
作者:
Chapman BE;Lee S;Kang HP;Chapman WW
In this paper we describe an application called peFinder for document-level classification of CT pulmonary angiography reports. peFinder is based on a generalized version of the ConText algorithm, a simple text processing algorithm for identifying features in clinical report documents. peFinder was used to answer questions about the disease state (pulmonary emboli present or absent), the certainty state of the diagnosis (uncertainty present or absent), the temporal state of an identified pulmonary embolus (acute or chronic), and the technical quality state of the exam (diagnostic or not diagnostic). Gold standard answers for each question were determined from the consensus classifications of three human annotators. peFinder results were compared to naive Bayes’ classifiers using unigrams and bigrams. The sensitivities (and positive predictive values) for peFinder were 0.98(0.83), 0.86(0.96), 0.94(0.93), and 0.60(0.90) for disease state, quality state, certainty state, and temporal state respectively, compared to 0.68(0.77), 0.67(0.87), 0.62(0.82), and 0.04(0.25) for the naive Bayes’ classifier using unigrams, and 0.75(0.79), 0.52(0.69), 0.59(0.84), and 0.04(0.25) for the naive Bayes’ classifier using bigrams.
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影响因子:
8.8
作者:
Kaushal, Rainu;Bates, David W.;Rothschild, Jeffrey M.
通讯作者:
Rothschild, Jeffrey M.
DOI:
10.1197/jamia.m1330
发表时间:
2003-09-01
影响因子:
6.4
作者:
Chapman, WW;Cooper, GF;Wagner, MM
通讯作者:
Wagner, MM
影响因子:
4.8
作者:
Abujudeh, Hani H.;Kaewlai, Rathachai;Shepard, Jo-Anne O.
通讯作者:
Shepard, Jo-Anne O.
影响因子:
4.5
作者:
Harkema H;Dowling JN;Thornblade T;Chapman WW
通讯作者:
Chapman WW
影响因子:
3.5
作者:
Gupta, D;Saul, M;Gilbertson, J
通讯作者:
Gilbertson, J