@InProceedings{yamashita-EtAl:2016:ClinicalNLP,
  author    = {Yamashita, Takanori  and  Wakata, Yoshifumi  and  Soejima, Hidehisa  and  Nakashima, Naoki  and  Hirokawa, Sachio},
  title     = {Prediction of Key Patient Outcome from Sentence and Word of Medical Text Records},
  booktitle = {Proceedings of the Clinical Natural Language Processing Workshop (ClinicalNLP)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {86--90},
  abstract  = {The number of unstructured medical records kept in hospital information systems
	is increasing.
	The conditions of patients are formulated as outcomes in clinical pathway.
	A variance of an outcome describes deviations from standards of care like a
	patient's bad condition. 
	The present paper applied text mining to extract feature words and phrases of
	the variance from admission records.
	We report the cases the variances of ``pain control'' and ``no neuropathy
	worsening'' in cerebral infarction.},
  url       = {http://aclweb.org/anthology/W16-4212}
}