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Extraction of Biomedical Events Related to Disease Based on Deep Parsing

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Biomedical events carry valuable biomedical knowledge. Extracting these biomedical events in text can help to explore disease pathogenesis. In this paper, we proposed an approach for extracting biomedical events related to disease based on deep parsing. Our proposed approach has a few advantages: (1) expanding tagged entities for complete semantic meaning, (2) extending trigger words of biomedical events by considering prepositions, (3) measuring dependent strength between participants of a biomedical event by point-wise mutual information, (4) visualizing extracted direct and indirect biomedical events with semantic network. We also developed a system using our proposed approach. To our best knowledge, it is the first application that offers the functionality of extracting direct and indirect biomedical events related to disease with semantic network visualization based on deep parsing. Experimental results show our approach is promising for developing biomedical event extraction system.

Keywords: BIOMEDICAL TEXT MINING; DEEP PARSING; EVENT EXTRACTION; NETWORK VISUALIZATION

Document Type: Research Article

Publication date: 01 November 2011

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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