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Syntactic-Semantic Frames for Clinical Cohort Identification Queries

  • Dina Demner-Fushman
  • Swapna Abhyankar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7348)

Abstract

Large sets of electronic health record data are increasingly used in retrospective clinical studies and comparative effectiveness research. The desired patient cohort characteristics for such studies are best expressed as free text descriptions. We present a syntactic-semantic approach to structuring these descriptions. We developed the approach on 60 training topics (descriptions) and evaluated it on 35 test topics provided within the 2011 TREC Medical Record evaluation. We evaluated the accuracy of the frames as well as the modifications needed to achieve near perfect precision in identifying the top 10 eligible patients. Our automatic approach accurately captured 34 test descriptions; 25 automatic frames needed no modifications for finding eligible patients. Further evaluations of the overall average retrieval effectiveness showed that frames are not needed for simple descriptions containing one or two key terms. However, our training results suggest that the frames are needed for more complex real-life cohort selection tasks.

Keywords

Test Question Clinical Cohort Electronic Health Record Data Information Retrieval Method Query Frame 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Dina Demner-Fushman
    • 1
  • Swapna Abhyankar
    • 1
  1. 1.National Library of MedicineBethesdaUSA

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