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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Summerscales, R.L. Argamon, S. Bai, S. Huperff, J. Schwartzff, A. |
| Copyright Year | 2011 |
| Abstract | 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. |
| Starting Page | 372 |
| Ending Page | 377 |
| File Size | 157253 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781457717994 |
| DOI | 10.1109/BIBM.2011.72 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-11-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Context summarization information extraction Semantics Abstracts Medical services Particle measurements Biomedical measurements Data mining medical text processing |
| Content Type | Text |
| Resource Type | Article |
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