An evaluation of natural language processing methodologies

Medical language processing (MLP) systems that codify information in textual patient reports have been developed to help solve the data entry problem. Some systems have been evaluated in order to assess performance, but there has been little evaluation of the underlying technology. Various methodolo...

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Veröffentlicht in:Proceedings. AMIA Symposium. - 1998. - (1998) vom: 13., Seite 855-9
1. Verfasser: Friedman, C (VerfasserIn)
Weitere Verfasser: Hripcsak, G, Shablinsky, I
Format: Aufsatz
Sprache:English
Veröffentlicht: 1998
Zugriff auf das übergeordnete Werk:Proceedings. AMIA Symposium
Schlagworte:Comparative Study Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S.
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520 |a Medical language processing (MLP) systems that codify information in textual patient reports have been developed to help solve the data entry problem. Some systems have been evaluated in order to assess performance, but there has been little evaluation of the underlying technology. Various methodologies are used by the different MLP systems but a comparison of the methods has not been performed although evaluations of MLP methodologies would be extremely beneficial to the field. This paper describes a study that evaluates different techniques. To accomplish this task an existing MLP system MedLEE was modified and results from a previous study were used. Based on confidence intervals and differences in sensitivity and specificity between each technique and all the others combined, the results showed that the two methods based on obtaining the largest well-formed segment within a sentence had significantly higher sensitivity than the others by 5% and 6%. The method based on recognizing a complete sentence had a significantly worse sensitivity than the others by 7% and a better specificity by .2%. None of the methods had significantly worse specificity 
650 4 |a Comparative Study 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
650 4 |a Research Support, U.S. Gov't, P.H.S. 
700 1 |a Hripcsak, G  |e verfasserin  |4 aut 
700 1 |a Shablinsky, I  |e verfasserin  |4 aut 
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