@InProceedings{campillosllanos-rosset-zweigenbaum:2017:BioNLP17,
  author    = {Campillos Llanos, Leonardo  and  Rosset, Sophie  and  Zweigenbaum, Pierre},
  title     = {Automatic classification of doctor-patient questions for a virtual patient record query task},
  booktitle = {BioNLP 2017},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada,},
  publisher = {Association for Computational Linguistics},
  pages     = {333--341},
  abstract  = {We present the work-in-progress of automating the classification of
	doctor-patient questions in the context of a simulated consultation with a
	virtual patient. We classify questions according to the computational strategy
	(rule-based or other) needed for looking up data in the clinical record. We
	compare ‘traditional’ machine learning methods (Gaussian and Multinomial
	Naive Bayes, and Support Vector Machines) and a neural network classifier
	(FastText). We obtained the best results with the SVM using semantic
	annotations, whereas the neural classifier achieved promising results without
	it.},
  url       = {http://www.aclweb.org/anthology/W17-2343}
}