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By Matthew S. Simpson and Dina Demner-fushman


The biomedical community makes extensive use of text mining technology. In the past several years, enormous progress has been made in developing tools and methods, and the community has been witness to some exciting developments. Although the state of the community is regularly reviewed, the sheer volume of work related to biomedical text mining and the rapid pace in which progress continues to be made make this a worthwhile, if not necessary, endeavor. This chapter provides a brief overview of the current state of text mining in the biomedical domain. Emphasis is placed on the resources and tools available to biomedical researchers and practitioners, as well as the major text mining tasks of interest to the community. These tasks include the recognition of explicit facts from biomedical literature, the discovery of previously unknown or implicit facts, document summarization, and question answering. For each topic, its basic challenges and methods are outlined and recent and influential work is reviewed.

Topics: Biomedical information extraction, named entity recognition, relations, events, summarization, question answering, literature-based discovery
Publisher: 2013-09-21
Year: 2013
OAI identifier: oai:CiteSeerX.psu:
Provided by: CiteSeerX
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