@InProceedings{dernoncourt-lee-szolovits:2017:EACLshort,
  author    = {Dernoncourt, Franck  and  Lee, Ji Young  and  Szolovits, Peter},
  title     = {Neural Networks for Joint Sentence Classification in Medical Paper Abstracts},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {694--700},
  abstract  = {Existing models based on artificial neural networks (ANNs) for sentence
	classification often do not incorporate the context in which sentences appear,
	and classify sentences individually. However, traditional sentence
	classification approaches have been shown to greatly benefit from jointly
	classifying subsequent sentences, such as with conditional random fields. In
	this work, we present an ANN architecture that combines the effectiveness of
	typical ANN models to classify sentences in isolation, with the strength of
	structured prediction. Our model outperforms the state-of-the-art results on
	two different datasets for sequential sentence classification in medical
	abstracts.},
  url       = {http://www.aclweb.org/anthology/E17-2110}
}