DocumentCode
2890962
Title
Automatic Summarization of Results from Clinical Trials
Author
Summerscales, Rodney L. ; Argamon, Shlomo ; Bai, Shangda ; Huperff, Jordan ; Schwartz, Alan
Author_Institution
Dept. of Comput. Sci., Illinois Inst. of Technol., Chicago, IL, USA
fYear
2011
fDate
12-15 Nov. 2011
Firstpage
372
Lastpage
377
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.
Keywords
abstracting; medical computing; statistical analysis; absolute risk reduction; automatic summarization; biomedical research; clinical trials; evidence based medicine; key summary statistics; manual summarization; number needed to treat; randomly-controlled trials; research abstracts; Abstracts; Biomedical measurements; Context; Data mining; Medical services; Particle measurements; Semantics; information extraction; medical text processing; summarization;
fLanguage
English
Publisher
ieee
Conference_Titel
Bioinformatics and Biomedicine (BIBM), 2011 IEEE International Conference on
Conference_Location
Atlanta, GA
Print_ISBN
978-1-4577-1799-4
Type
conf
DOI
10.1109/BIBM.2011.72
Filename
6120468
Link To Document