| Title |
Final Diagnosis Classification using Fine-tune BERT for Automatic Labeling |
| Authors |
안경진(Kyeongjin Ann) ; 장영걸(Yeonggul Jang) ; 홍영택(Youngtaek Hong) ; 정성희(Sunghee Jung) ; 심학준(Hackjoon Shim) ; 장혁재(Hyuk-Jae Chang) |
| DOI |
https://doi.org/10.5573/ieie.2019.56.12.92 |
| Keywords |
Medical ; Final Diagnosis ; Classification ; Pre-training ; BERT ; |
| Abstract |
Recently, many studies have been underway to provide better medical technology by applying artificial intelligence technology in the medical field. Building training data for learning artificial intelligence is a necessary process because it requires a sufficient number of medical data and corresponding labels. However, large numbers of medical data labeling is labor-intensive issue, which has increased the need for automatic labeling. In this paper, we will introduce the study of automatically labeling the final diagnosis in medical treatment record using the BERT model, which shows the best performance in natural language processing in recent years |