Extracting clinical trial design information from MEDLINE abstracts

Authors:
Kazuo Hara;Yuji Matsumoto
Affiliations:
Nara Institute of Science and Technology, Graduate School of Information Science, Computational Linguistics Laboratory, Takayama, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Graduate School of Information Science, Computational Linguistics Laboratory, Takayama, Ikoma, Nara, Japan
Venue:
New Generation Computing
Year:
2007

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Abstract

Evidence-based medicine (EBM) requires medical practitioners to select appropriate treatments for individual patients based on the current best evidence, and the results of phase III clinical trials are the major source of such evidence. In this paper, we report results of experiment in extracting important information for EBM from the abstracts of phase III clinical trials, in an effort to investigate how far the existing natural language processing (NLP) techniques could support EBM using MEDLINE database.