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Exploring Radiographers' Readiness for Artificial Intelligence in Kuwait: Insights and Applications
Asseel Khalaf1, Manar Alshammari2, Hawraa Zayed3
1Radiologic Sciences Department, Faculty of Allied Health Sciences Kuwait University Kuwait City Kuwait.
Health Science Reports
|March 31, 2025
Summary
Radiographers are eager to learn artificial intelligence (AI) for medical imaging, but education is needed. AI shows promise in generating chest reports, though accuracy requires further development.
Area of Science:
- Medical Imaging
- Artificial Intelligence
- Radiography
Background:
- Artificial intelligence (AI) adoption is increasing in medical imaging.
- AI offers potential benefits for patient care, workflow optimization, and data analysis.
- Radiographers' perspectives on AI integration are crucial for successful implementation.
Purpose of the Study:
- To explore radiographers' knowledge, perceptions, and expectations regarding AI in medical imaging.
- To evaluate an AI-based software for generating chest radiology reports.
- To assess the accuracy of AI-generated reports compared to radiologist assessments.
Main Methods:
- A cross-sectional survey was administered to 50 radiographers to assess AI knowledge and perceptions.
- A retrospective analysis involved 40 chest radiographs analyzed by AI software (Siemens).
- A radiologist evaluated the accuracy of AI-generated reports using a Likert scale.
Main Results:
- 98% of radiographers believe they must adapt to AI technology, with 92% interested in AI training.
- Radiographers' opinions on AI correlated significantly with their perceptions of AI education (p < 0.05).
- Radiologists agreed with 53% of the AI-generated chest reports, indicating room for improvement.
Conclusions:
- There is a clear demand for AI education and training among radiographers.
- AI-powered tools demonstrate significant potential in advancing medical imaging analysis.
- Further research and development are needed to enhance the accuracy and integration of AI in clinical practice.
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