@InProceedings{miller-EtAl:2017:BioNLP17,
  author    = {Miller, Timothy  and  Bethard, Steven  and  Amiri, Hadi  and  Savova, Guergana},
  title     = {Unsupervised Domain Adaptation for Clinical Negation Detection},
  booktitle = {BioNLP 2017},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada,},
  publisher = {Association for Computational Linguistics},
  pages     = {165--170},
  abstract  = {Detecting negated concepts in clinical texts is an important part of NLP
	information extraction systems. However, generalizability of negation systems
	is lacking, as cross-domain experiments suffer dramatic performance losses. We
	examine the performance of multiple unsupervised domain adaptation algorithms
	on clinical negation detection, finding only modest gains that fall well short
	of in-domain performance.},
  url       = {http://www.aclweb.org/anthology/W17-2320}
}