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Are we sleepwalking into a fully automated medical imaging service?
1Department of Medical Imaging, University of Exeter, St Luke's Campus, Heavitree Road, Exeter EX1 2LU, United Kingdom.
Introduction:
Artificial intelligence (AI) is already embedded in medical imaging services, but now that the National Institute for Health and Care Excellence (NICE) has released position statements looking favourably on AI use in healthcare, its use will embed even further.
Discussion:
AI has brought many positives to medical imaging services and is far superior at making calculations using vast amounts of data. It can therefore help improve the speed and accuracy of diagnosis and treatment plans for many patients, but at what cost to the radiography profession? Surveys have shown that the majority of the workforce welcome AI, but admit that they don't fully understand the principles behind it. AI developers are keen to improve patient output, and many are unconcerned about the possible negative effects on staff morale and expertise. As computers remove the autonomy and competency that radiographers have previously held with pride, staff may find that they become de-skilled and de-motivated, and it may eventually subsume the traditional role of the radiographer altogether. The profession needs to be aware of these potential impacts and prepare accordingly.
Conclusion:
Higher education plays an important role in preparing radiographers of the future for the changing landscape of medical imaging and should include more engineering and data science modules in the curriculum to prevent radiographers from becoming irrelevant.
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