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

arXiv 2403.16158 ↗First posted 24 Mar 2024cs.CLcited by 0

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Abstract (arXiv)

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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References · 12

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  5. 2020HunFlair: An Easy-to-Use Tool for State-of-the-Art Biomedical Named Entity Recognitioncited by 26
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  10. 2019Healthcare NER Models Using Language Model Pretrainingcited by 8
  11. 2020SemClinBr -- a multi institutional and multi specialty semantically annotated corpus for Portuguese clinical NLP taskscited by 7
  12. 2021Named Entity Recognition in Unstructured Medical Text Documentscited by 3

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