CLJun 26, 2016

Learning for Biomedical Information Extraction: Methodological Review of Recent Advances

arXiv:1606.07993v160 citations
Originality Synthesis-oriented
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It provides a targeted methodological review for researchers in biomedical informatics, but is incremental as it builds on existing reviews by focusing on specific techniques.

This review focuses on recent advances in learning-based approaches for biomedical information extraction, systematically summarizing methodological developments and exploring open information extraction and deep learning as emerging techniques.

Biomedical information extraction (BioIE) is important to many applications, including clinical decision support, integrative biology, and pharmacovigilance, and therefore it has been an active research. Unlike existing reviews covering a holistic view on BioIE, this review focuses on mainly recent advances in learning based approaches, by systematically summarizing them into different aspects of methodological development. In addition, we dive into open information extraction and deep learning, two emerging and influential techniques and envision next generation of BioIE.

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