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Information 2015, 6(4), 790-810; doi:10.3390/info6040790

Drug Name Recognition: Approaches and Resources

Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, 518055 Shenzhen, China
These authors contributed equally to this work.
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Author to whom correspondence should be addressed.
Academic Editor: Willy Susilo
Received: 15 October 2015 / Revised: 13 November 2015 / Accepted: 19 November 2015 / Published: 25 November 2015
(This article belongs to the Section Information Theory and Methodology)
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Abstract

Drug name recognition (DNR), which seeks to recognize drug mentions in unstructured medical texts and classify them into pre-defined categories, is a fundamental task of medical information extraction, and is a key component of many medical relation extraction systems and applications. A large number of efforts have been devoted to DNR, and great progress has been made in DNR in the last several decades. We present here a comprehensive review of studies on DNR from various aspects such as the challenges of DNR, the existing approaches and resources for DNR, and possible directions. View Full-Text
Keywords: drug name recognition; drug information extraction; biomedical texts drug name recognition; drug information extraction; biomedical texts
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Liu, S.; Tang, B.; Chen, Q.; Wang, X. Drug Name Recognition: Approaches and Resources. Information 2015, 6, 790-810.

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