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Occupation classification model based on DistilKoBERT: using the 5th and 6th Korean Working Condition Surveys.

Tae-Yeon KimSeong-Uk BaekMyeong-Hun LimByung-Yoon YunDomyung PaekKyung Ehi ZohKanwoo YounYun Keun LeeYangho KimJungwon KimEunsuk ChoiMo-Yeol KangYoonho ChoKyeong-Eun LeeJu Ho SimJuyeon OhHeejoo ParkJian LeeJong-Uk WonYu-Min LeeJin Ha Yoon
Published in: Annals of occupational and environmental medicine (2024)
This study developed an occupation classification system based on DistilKoBERT, which demonstrated reasonable performance. Despite further efforts to enhance the classification accuracy, this automated occupation classification model holds promise for advancing epidemiological studies in the fields of occupational safety and health.
Keyphrases
  • deep learning
  • machine learning
  • healthcare
  • big data
  • artificial intelligence
  • public health
  • mental health
  • high throughput
  • health information
  • quality improvement
  • climate change
  • social media
  • risk assessment
  • single cell