@inproceedings{wang-etal-2020-studying,
    title = "Studying Challenges in Medical Conversation with Structured Annotation",
    author = "Wang, Nan  and
      Song, Yan  and
      Xia, Fei",
    editor = "Bhatia, Parminder  and
      Lin, Steven  and
      Gangadharaiah, Rashmi  and
      Wallace, Byron  and
      Shafran, Izhak  and
      Shivade, Chaitanya  and
      Du, Nan  and
      Diab, Mona",
    booktitle = "Proceedings of the First Workshop on Natural Language Processing for Medical Conversations",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.nlpmc-1.3/",
    doi = "10.18653/v1/2020.nlpmc-1.3",
    pages = "12--21",
    abstract = "Medical conversation is a central part of medical care. Yet, the current state and quality of medical conversation is far from perfect. Therefore, a substantial amount of research has been done to obtain a better understanding of medical conversation and to address its practical challenges and dilemmas. In line with this stream of research, we have developed a multi-layer structure annotation scheme to analyze medical conversation, and are using the scheme to construct a corpus of naturally occurring medical conversation in Chinese pediatric primary care setting. Some of the preliminary findings are reported regarding 1) how a medical conversation starts, 2) where communication problems tend to occur, and 3) how physicians close a conversation. Challenges and opportunities for research on medical conversation with NLP techniques will be discussed."
}