TITLE

Knowledge-based Methods to Help Clinicians Find Answers in MEDLINE

AUTHOR(S)
Sneiderman, Charles A.; Demner-Fushman, Dina; Fiszman, Marcelo; Ide, Nicholas C.; Rindflesch, Thomas C.
PUB. DATE
November 2007
SOURCE
Journal of the American Medical Informatics Association;Nov/Dec2007, Vol. 14 Issue 6, p772
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Objectives: Large databases of published medical research can support clinical decision making by providing physicians with the best available evidence. The time required to obtain optimal results from these databases using traditional systems often makes accessing the databases impractical for clinicians. This article explores whether a hybrid approach of augmenting traditional information retrieval with knowledge-based methods facilitates finding practical clinical advice in the research literature. Design: Three experimental systems were evaluated for their ability to find MEDLINE citations providing answers to clinical questions of different complexity. The systems (SemRep, Essie, and CQA-1.0), which rely on domain knowledge and semantic processing to varying extents, were evaluated separately and in combination. Fifteen therapy and prevention questions in three categories (general, intermediate, and specific questions) were searched. The first l0 citations retrieved by each system were randomized, anonymized, and evaluated on a three-point scale. The reasons for ratings were documented. Measurements: Metrics evaluating the overall performance of a system (mean average precision, binary preference) and metrics evaluating the number of relevant documents in the first several presented to a physician were used. Results: Scores (mean average precision = 0.57, binary preference = 0.71) for fusion of the retrieval results of the three systems are significantly (p < 0.01) better than those for any individual system. All three systems present three to four relevant citations in the first five for any question type. Conclusion: The improvements in finding relevant MEDLINE citations due to knowledge-based processing show promise in assisting physicians to answer questions in clinical practice.
ACCESSION #
27671456

 

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