@InProceedings{brokos-EtAl:2018:BioASQ,
  author    = {Brokos, George  and  Liosis, Polyvios  and  McDonald, Ryan  and  Pappas, Dimitris  and  Androutsopoulos, Ion},
  title     = {AUEB at BioASQ 6: Document and Snippet Retrieval},
  booktitle = {Proceedings of the 6th BioASQ Workshop A challenge on large-scale biomedical semantic indexing and question answering},
  month     = {November},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {30--39},
  abstract  = {We present system details for AUEB’s submissions to the BioASQ 6 Document and Snippet Retrieval challenge (Task 6b Phase A). Our models use novel extensions to deep learning architectures that operate solely over the text of the query and candidate document/snippets. Overall, our systems scored at the top or near the top for all batches and metrics of the challenge, highlighting the effectiveness of deep learning for the task.},
  url       = {http://www.aclweb.org/anthology/W18-5304}
}