Journal of radiological science and technology (대한방사선기술학회지:방사선기술과학)

Korean Society of Radiological Science (대한방사선과학회)
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Utilizing the Orange Platform for Enhancing Artificial Intelligence Education in the Department of Radiological Science at Universities

대학 방사선학과 인공지능 교육 활성화를 위한 Orange 플랫폼 이용 사례

  • Kyoungho Choi (Department of Radiological Science/Research Institute of Health Statistics, College of Medical Sciences, Jeonju University)
  • 최경호 (전주대학교 의과학대학 방사선학과/보건통계연구소)
  • Received : 2024.05.30
  • Accepted : 2024.06.27
  • Published : 2024.08.31
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Abstract

Although a universally accepted definition of artificial intelligence (AI) remains elusive, the terminology has gained widespread familiarity owing to its pervasive integration across diverse domains in our daily lives. The application of AI in healthcare, notably in radiographic imaging, is no longer a matter of science fiction but a reality. Consequently, AI education has emerged as an indispensable requirement for radiological technologists responsible for the field of radiology. This paper underscores this imperative and advocates for the incorporation of AI education, using the Orange platform in university radiology department as part of the solution. Furthermore, this paper presents a case study featuring machine learning analysis using structured data on exposure doses for radiation related workers and unstructured data consisting of X-ray data encompassing 69 COVID-19-infected cases and 25 individuals with normal findings. The emphasized importance of AI education for radiology professionals in this research is expected to contribute to the job stability of radiologic practitioners in the future.

Keywords

Acknowledgement

This work was supported by the 2024 research-year grant of Jeonju university.

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