Title:
Syntactic-Semantic Frames For Clinical Cohort
Identification Queries.
Author(s):
Demner-Fushman D, Abhyankar S.
Institution(s):
1) National Library of Medicine, Bethesda, MD
Source:
Lecture Notes in Computer Science. 2012;7348:100-112.
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.
Publication Type: JOURNAL
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