대한영상의학회지 (Journal of the Korean Society of Radiology)

  • 제81권6호
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  • Pages.1397-1411
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  • 2020
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  • 1738-2637(pISSN)
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  • 2951-0805(eISSN)
대한영상의학회 (The Korean Society of Radiology)
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의료 인공지능에 대한 대한민국 영상의학과 전공의의 인식 조사 연구

Survey of the Knowledge of Korean Radiology Residents on Medical Artificial Intelligence

  • 이현빈 (고려대학교 안산병원 영상의학과) ;
  • 박성호 (울산대학교 의과대학 서울아산병원 영상의학과, 영상의학과 연구소) ;
  • 김채리 (고려대학교 안산병원 영상의학과) ;
  • 김승관 (고려대학교 안산병원 영상의학과) ;
  • 차재형 (고려대학교 의과대학 의과학연구지원센터)
  • Hyeonbin Lee (Department of Radiology, Korea University Ansan Hospital) ;
  • Seong Ho Park (Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center) ;
  • Cherry Kim (Department of Radiology, Korea University Ansan Hospital) ;
  • Seungkwan Kim (Department of Radiology, Korea University Ansan Hospital) ;
  • Jaehyung Cha (Medical Science Research Center, Korea University College of Medicine)
  • 투고 : 2019.11.01
  • 심사 : 2020.02.23
  • 발행 : 2020.11.01
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초록

목적 이 연구는 인공지능(artificial intelligence; 이하 AI)에 대한 영상의학과 전공의들의 인식 및 의견을 알아보고자 하였다. 대상과 방법 2019년 6월 4일부터 7일까지 AI와 관련한 18개의 객관식 문항과 1개의 주관식 문항이 포함된 설문의 응답을 받았다. 모집된 결과를 로지스틱 회귀분석을 이용하여 전공의 연차, 소속 병원의 위치 및 규모 등의 요인에 따라 분석하였다. 결과 총 101명(89.4%)의 전공의가 응답하였다. AI의 지식적 측면에서 응답자의 50명(49.5%)이 AI에 대해 평균 이상으로 공부하고 있으며, 68명(67.3%)이 AI 관련 용어에 대한 이해도가 평균 이상이라고 응답하였다. 또한 서울 및 경기 지역 응답자가 기타 지역 응답자에 비하여 AI에 대한 자가 평가 및 지식수준이 의미 있게 높았으며, 4년차 전공의에 비해 1~2년차 전공의가 AI에 대한 자가 평가 및 지식수준이 의미 있게 낮았다. AI 관련 연구에 참여해본 적 있는 전공의는 15.8%이었지만, 추후 연구 참여 의향이 있는 전공의는 90%에 달하였다. 전공의 들은 또한 학회 주도의 AI 교육 및 적극적 홍보를 원하고 있었다. 결론 영상의학과 전공의의 AI 교육 수요를 충족시키고, 의료 AI 시대의 영상의학과 의사의 역할을 제대로 알리기 위해 보다 많은 학회 차원의 노력이 요청된다.

Purpose To survey the perception, knowledge, wishes, and expectations of Korean radiology residents regarding artificial intelligence (AI) in radiology. Materials and Methods From June 4th to 7th, 2019, questionnaires comprising 19 questions related to AI were distributed to 113 radiology residents. Results were analyzed based on factors such as the year of residency and location and number of beds of the hospital. Results A total of 101 (89.4%) residents filled out the questionnaire. Fifty (49.5%) respondents had studied AI harder than the average while 68 (67.3%) had a similar or higher understanding of AI than the average. In addition, the self-evaluation and knowledge level of AI were significantly higher for radiology residents at hospitals located in Seoul and Gyeonggi-do compared to radiology residents at hospitals located in other regions. Furthermore, the self-evaluation and knowledge level of AI were significantly lower in junior residents than in residents in the 4th year of training. Of the 101 respondents, only 16 (15.8%) had experiences in AI-related study while 91 (90%) were willing to participate in AI-related study in the future. Conclusion Organizational efforts through a radiology society would be needed to meet the need of radiology trainees for AI education and to promote the role of radiologists more adequately in the era of medical AI.

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