In Journal of medical imaging and radiation sciences
Artificial intelligence (AI) and machine learning (ML) approaches have caught the attention of many in health care. Current literature suggests there are many potential benefits that could transform future clinical workflows and decision making. Embedding AI and ML concepts in radiation therapy education could be a fundamental step in equipping radiation therapists (RTs) to engage in competent and safe practice as they utilise clinical technologies. In this discussion paper, the authors provide a brief review of some applications of AI and ML in radiation therapy and discuss pertinent considerations for radiation therapy curriculum enhancement. As the current literature suggests, AI and ML approaches will impose changes to routine clinical radiation therapy tasks. The emphasis in RT education could be on critical evaluation of AI and ML application in routine clinical workflows and gaining an understanding of the impact on quality assurance, provision of quality of care and safety in radiation therapy as well as research. It is also imperative RTs have a broader understanding of AI/ML impact on health care, including ethical and legal considerations. The paper concludes with recommendations and suggestions to deliberately embed AI and ML aspects in RT education to empower future RT practitioners.
Chamunyonga Crispen, Edwards Christopher, Caldwell Peter, Rutledge Peta, Burbery Julie
Radiation therapist, artificial intelligence, education, machine learning