@InProceedings{cotik-EtAl:2017:RANLP,
  author    = {Cotik, Viviana  and  Filippo, Dar\'{i}o  and  Roller, Roland  and  Uszkoreit, Hans  and  Xu, Feiyu},
  title     = {Annotation of Entities and Relations in Spanish Radiology Reports},
  booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017},
  month     = {September},
  year      = {2017},
  address   = {Varna, Bulgaria},
  publisher = {INCOMA Ltd.},
  pages     = {177--184},
  abstract  = {Radiology reports express the results of a radiology study and contain
	information about anatomical entities, findings, measures and impressions of
	the medical doctor. The use of information extraction techniques can help
	physicians to access this information in order to understand data and to infer
	further knowledge. 
	Supervised machine learning methods are very popular to address information
	extraction, but are usually domain and language dependent. To train new
	classification models, annotated data is required. Moreover, annotated data is
	also required as an evaluation resource of information extraction algorithms.
	However, one major drawback of processing clinical data is the low availability
	of annotated datasets. For this reason we performed a manual annotation of
	radiology reports written in Spanish. This paper presents the corpus, the
	annotation schema, the annotation guidelines and further insight of the data.},
  url       = {https://doi.org/10.26615/978-954-452-049-6_025}
}