@inproceedings{byun-etal-2024-korean,
    title = "{K}orean Bio-Medical Corpus ({KBMC}) for Medical Named Entity Recognition",
    author = "Byun, Sungjoo  and
      Hong, Jiseung  and
      Park, Sumin  and
      Jang, Dongjun  and
      Seo, Jean  and
      Kim, Minseok  and
      Oh, Chaeyoung  and
      Shin, Hyopil",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.868",
    pages = "9941--9947",
    abstract = "Named Entity Recognition (NER) plays a pivotal role in medical Natural Language Processing (NLP). Yet, there has not been an open-source medical NER dataset specifically for the Korean language. To address this, we utilized ChatGPT to assist in constructing the KBMC (Korean Bio-Medical Corpus), which we are now presenting to the public. With the KBMC dataset, we noticed an impressive 20{\%} increase in medical NER performance compared to models trained on general Korean NER datasets. This research underscores the significant benefits and importance of using specialized tools and datasets, like ChatGPT, to enhance language processing in specialized fields such as healthcare.",
}

Named Entity Recognition (NER) plays a pivotal role in medical Natural Language Processing (NLP). Yet, there has not been an open-source medical NER dataset specifically for the Korean language. To address this, we utilized ChatGPT to assist in constructing the KBMC (Korean Bio-Medical Corpus), which we are now presenting to the public. With the KBMC dataset, we noticed an impressive 20{\%} increase in medical NER performance compared to models trained on general Korean NER datasets. This research underscores the significant benefits and importance of using specialized tools and datasets, like ChatGPT, to enhance language processing in specialized fields such as healthcare.
Byun, Sungjoo Hong, Jiseung Park, Sumin Jang, Dongjun Seo, Jean Kim, Minseok Oh, Chaeyoung Shin, Hyopil
Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition