Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition

Sungjoo Byun, Jiseung Hong, Sumin Park, Dongjun Jang, Jean Seo +3 more
3/24/2024
cs.CL

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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.

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Cite this paper

@article{byun2024korean,
  title  = {Korean Bio-Medical Corpus (KBMC) for Medical Named Entity Recognition},
  author = {Sungjoo Byun and Jiseung Hong and Sumin Park and Dongjun Jang and Jean Seo and Minseok Kim and Chaeyoung Oh and Hyopil Shin},
  year   = {2024},
  eprint = {2403.16158},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.16158v1}
}

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