@article{liu_learning_2016,
	title = {Learning for {Biomedical} {Information} {Extraction}: {Methodological} {Review} of {Recent} {Advances}},
	url = {https://arxiv.org/ftp/arxiv/papers/1606/1606.07993.pdf},
	abstract = {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.},
	journal = {arXiv:1606.07993},
	author = {Liu, Feifan and Chen, Jinying and Jagannatha, Abhyuday and Yu, Hong},
	month = jun,
	year = {2016},
}

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