Journal of Korean Society of Occupational and Environmental Hygiene (한국산업보건학회지)

Korean Industrial Hygiene Association (한국산업보건학회)
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Development of an AI Model to Determine the Relationship between Cerebrovascular Disease and the Work Environment as well as Analysis of Consistency with Expert Judgment

뇌심혈관 질환과 업무 환경의 연관성 판단을 위한 AI 모델의 개발 및 전문가 판단과의 일치도 분석

  • Juyeon Oh (Department of Public Health, Graduate School, Yonsei University) ;
  • Ki-bong Yoo (Department of Health Administration, Yonsei University) ;
  • Ick Hoon Jin (Department of Applied Statistics, Yonsei University) ;
  • Byungyoon Yun (Department of Occupational Health, Department of Preventive Medicine, Yonsei University College of Medicine) ;
  • Juho Sim (Department of Occupational Health, Department of Preventive Medicine, Yonsei University College of Medicine) ;
  • Heejoo Park (Department of Public Health, Graduate School, Yonsei University) ;
  • Jongmin Lee (Department of Occupational Health, Graduate School of Public Health, Yonsei University) ;
  • Jian Lee (Department of Public Health, Graduate School, Yonsei University) ;
  • Jin-Ha Yoon (Department of Occupational Health, Department of Preventive Medicine, Yonsei University College of Medicine)
  • 오주연 (연세대학교 일반대학원 보건학과) ;
  • 유기봉 (연세대학교 보건행정학부) ;
  • 진익훈 (연세대학교 응용통계학과) ;
  • 윤병윤 (연세대학교 의과대학 예방의학교실) ;
  • 심주호 (연세대학교 의과대학 예방의학교실) ;
  • 박희주 (연세대학교 일반대학원 보건학과) ;
  • 이종민 (연세대학교 보건대학원 산업보건전공) ;
  • 이지안 (연세대학교 일반대학원 보건학과) ;
  • 윤진하 (연세대학교 의과대학 예방의학교실)
  • Received : 2024.04.09
  • Accepted : 2024.09.11
  • Published : 2024.09.30
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Abstract

Introduction: Acknowledging the global issue of diseases potentially caused by overwork, this study aims to develop an AI model to help workers understand the connection between cerebrocardiovascular diseases and their work environment. Materials and methods: The model was trained using medical and legal expertise along with data from the 2021 occupational disease adjudication certificate by the Industrial Accident Compensation Insurance and Prevention Service. The Polyglot-ko-5.8B model, which is effective for processing Korean, was utilized. Model performance was evaluated through accuracy, precision, sensitivity, and F1-score metrics. Results: The model trained on a comprehensive dataset, including expert knowledge and actual case data, outperformed the others with respective accuracy, precision, sensitivity, and F1-scores of 0.91, 0.89, 0.84, and 0.87. However, it still had limitations in responding to certain scenarios. Discussion: The comprehensive model proved most effective in diagnosing work-related cerebrocardiovascular diseases, highlighting the significance of integrating actual case data in AI model development. Despite its efficacy, the model showed limitations in handling diverse cases and offering health management solutions. Conclusion: The study succeeded in creating an AI model to discern the link between work factors and cerebrocardiovascular diseases, showcasing the highest efficacy with the comprehensively trained model. Future enhancements towards a template-based approach and the development of a user-friendly chatbot webUI for workers are recommended to address the model's current limitations.

Keywords

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