This gap points to a training opportunity, wrote a team led by Mohamed Abuzaid, PhD, of the University of Sharjah in the United Arab Emirates.
"The knowledge gap requires collaboration between educational institutes and professional bodies to develop structured [AI] training programs for radiologists and radiographers," Abuzaid and colleagues wrote.
Incorporating AI into medical imaging could lead to "significant advances in the practice of radiology," the authors noted. But just how knowledgeable are radiologists and radiographers about AI?
The researchers addressed this question via a questionnaire distributed to 272 participants that explored their knowledge, perception, and readiness regarding integrating AI into radiology practice. Of the 272 invited participants, 153 responded; of these, 77.8% were radiographers and 22.2% were radiologists.
When it came to perceptions about AI, the group found survey participants were mixed:
- 32% of survey respondents expressed enthusiasm about AI, but 85.6% disagreed with the statement "AI will play an important role in the practice of radiology professionals."
- 34% stated they did not have enough information about AI, were worried about its effects, or were neutral.
- 16.3% agreed that "AI will threaten/disrupt the practice of radiology professionals."
In terms of knowledge about AI, Abuzaid and colleagues found that almost 40% of respondents were not familiar with the technology -- in fact, 74.5% had not studied AI during their educational degree work. Only 15.7% of study participants stated they were "comfortable with what AI means" but had no technical information about it.
|Survey responses to the question: "How well do you understand what is meant by AI?"
|I've no idea
||I'm familiar with AI basics
||I'm comfortable with what it means, but I'm not technical
||Very comfortable: I work with AI
"There seems to be a mismatch between awareness of the potential of AI and the expectations about its role," the authors wrote. "It's unclear if this is due to the way AI is practiced in the local radiology environment where the workforce fails to see a possible role ... [or if it is due] to the lack of proper and in-depth understanding of how AI can be implemented and what it can achieve beyond the widespread perception of sorting normal from abnormal x-ray cases."
The challenges to integrating AI into radiology practice need to be addressed for this integration to be successful, according to the group.
"We strongly recommend proper educational courses and instructional workshops from independent sources rather than just software vendors," the team concluded.
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