Radiography students' perceptions of artificial intelligence in medical imaging
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(Published version)
Date
2024
Authors
Arruzza, E.
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Journal article
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Journal of Medical Imaging and Radiation Sciences, 2024; 55(2):258-263
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Abstract
Introduction: Education relating to Artificial Intelligence (AI) is becoming critical to developing contemporary radiographers. This study sought to investigate the perceptions of a sample of Australian radiography students regarding AI within the context of medical imaging
Methods: Radiography students completed a cross-sectional online questionnaire which obtained quantitative and qualitative data relating to their perceptions and attitudes of AI within the radiographic context. Descriptive and inferential statistics were utilised, and thematic analysis was undertaken for open-text responses.
Results: Responses were gathered from twenty-five participants, in their second, third and fourth year of study. Most participants demonstrated a positive attitude towards AI. Most students view AI to be an assistive tool, though the cohort was less convinced AI would increase future employment in the industry. Females were more likely to disagree that AI will increase work opportunities for the radiographer (p = 0.021), as well as those in their final year of study (p = 0.011). Perceived benefits of AI related to improved work efficiency and image quality. Negative perceptions of AI involved reduced job security, and potential impact on patient care and safety.
Discussion: Students presented a multitude of positive and negative perceptions towards the role that AI may play in their future careers. Education pertaining to AI is central to transforming future clinical practice, and it is encouraging that undergraduate students are intrigued and willing to learn about AI in the radiographic context.
Conclusion: This study offers insight into the current perspectives of Australian radiography students on AI within medical imaging, to assist in implementation of future AI-related education in the undergraduate setting.
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Data source: Supplementary materials, https://doi.org/10.1016/j.jmir.2024.02.014
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Copyright 2024 Published by Elsevier Inc. on behalf of Canadian Association of Medical Radiation Technologists
Access Condition Notes: Accepted manuscript available after 01/04/2025