@InProceedings{gutierrez-EtAl:2017:EMNLP2017,
  author    = {Gutierrez, E. Dario  and  Cecchi, Guillermo  and  Corcoran, Cheryl  and  Corlett, Philip},
  title     = {Using Automated Metaphor Identification to Aid in Detection and Prediction of First-Episode Schizophrenia},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {2923--2930},
  abstract  = {The diagnosis of serious mental health conditions such as schizophrenia is
	based on the judgment of clinicians whose training takes several years, and
	cannot be easily formalized into objective measures. However, previous research
	suggests there are disturbances in aspects of the language use of patients with
	schizophrenia.                                      
	Using metaphor-identification and sentiment-analysis
	algorithms to automatically generate features, we create a classifier,               
	     
	that,
	with high
	accuracy, can predict which patients will develop (or currently suffer from)
	schizophrenia.                                      
	To our knowledge, this study is the first to demonstrate
	the utility of automated metaphor identification algorithms for detection or
	prediction of disease.},
  url       = {https://www.aclweb.org/anthology/D17-1316}
}