@inproceedings{bagherzadeh-bergler-2020-clac,
    title = "{CL}a{C} at {SMM}4{H} 2020: Birth Defect Mention Detection",
    author = "Bagherzadeh, Parsa  and
      Bergler, Sabine",
    editor = "Gonzalez-Hernandez, Graciela  and
      Klein, Ari Z.  and
      Flores, Ivan  and
      Weissenbacher, Davy  and
      Magge, Arjun  and
      O'Connor, Karen  and
      Sarker, Abeed  and
      Minard, Anne-Lyse  and
      Tutubalina, Elena  and
      Miftahutdinov, Zulfat  and
      Alimova, Ilseyar",
    booktitle = "Proceedings of the Fifth Social Media Mining for Health Applications Workshop {\&} Shared Task",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.smm4h-1.32/",
    pages = "168--170",
    abstract = "For the detection of personal tweets, where a parent speaks of a child{'}s birth defect, CLaC combines ELMo word embeddings and gazetteer lists from external resources with a GCNN (for encoding dependencies), in a multi layer, transformer inspired architecture. To address the task, we compile several gazetteer lists from resources such as MeSH and GI. The proposed system obtains .69 for {\ensuremath{\mu}}F1 score in the SMM4H 2020 Task 5 where the competition average is .65."
}