Patient perspectives on AI in radiology: Insights from the United Arab Emirates
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Published on: February 23, 2024
Mohamed Zakaria El-Sayed1, Mohammad Rawashdeh2, Aysha Moossa1
1Medical Imaging Sciences, College of Health Sciences, Gulf Medical University, Ajman, United Arab Emirates.
Rationale And Objectives:
Artificial intelligence (AI) enhances diagnostic accuracy, efficiency, and patient outcomes in radiology. Patient acceptance is essential for successful integration. This study examines patient perspectives on AI in radiology within the UAE, focusing on their knowledge, attitudes, and perceived barriers. Understanding these factors can address concerns, improve trust, and guide patient-centered AI implementation. The findings aim to support effective AI adoption in healthcare.
Methods:
A cross-sectional study involving 205 participants undergoing radiological imaging in the UAE. Data was collected through an online questionnaire, developed based on a literature review, and pre-tested for reliability and validity. Non-probability sampling methods, including convenience and snowball sampling, were employed. The questionnaire assessed participants' knowledge, attitudes, and perceived barriers regarding AI in radiology. Data was analyzed, and categorical variables were expressed as frequencies and percentages.
Results:
Most participants (89.8 %) believed AI could improve diagnostic accuracy, and 87.8 % acknowledged its role in prioritizing urgent cases. However, only 22 % had direct experience with AI in radiology. While 81 % expressed comfort with AI-based technology, concerns about data security (80.5 %), lack of empathy in AI systems (82.9 %), and insufficient information about AI (85.8 %) were significant barriers. Additionally, (87.3 %) of participants were concerned about the cost of AI implementation. Despite these concerns, 86.3 % believed AI could improve the quality of radiological services, and 83.9 % were satisfied with its potential applications.
Conclusion:
UAE patients generally support AI in radiology, recognizing its potential for improved diagnostic accuracy. However, concerns about data security, empathy, and understanding of AI technologies necessitate improved patient education, transparent communication, and regulatory frameworks to foster trust and acceptance.
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