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Automatic Summarization of Results from Clinical Trials

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5 Author(s)
Summerscales, R.L. ; Dept. of Comput. Sci., Illinois Inst. of Technol., Chicago, IL, USA ; Argamon, S. ; Bai, S. ; Huperff, J.
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A central concern in Evidence Based Medicine (EBM) is how to convey research results effectively to practitioners. One important idea is to summarize results by key summary statistics that describe the effectiveness (or lack thereof) of a given intervention, specifically the absolute risk reduction (ARR) and number needed to treat (NNT). Manual summarization is slow and expensive, thus, with the exponential growth of the biomedical research literature, automated solutions are needed. In this paper, we present a novel method for automatically creating EBM-oriented summaries from research abstracts of randomly-controlled trials (RCTs). The system extracts descriptions of the treatment groups and outcomes, as well as various associated quantities, and then calculates summary statistics. Results on a hand-annotated corpus of research abstracts show promising, and potentially useful, results.

Published in:

Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on

Date of Conference:

12-15 Nov. 2011