Patient perspectives on AI in radiology: Insights from the United Arab Emirates

Area of Science:

• Radiology and Medical Imaging
• Artificial Intelligence in Healthcare
• Patient Acceptance Studies

Background:

• Artificial intelligence (AI) offers significant potential to enhance diagnostic accuracy, efficiency, and patient outcomes in radiology.
• Patient acceptance is a critical factor for the successful integration of AI technologies in clinical practice.
• Understanding patient perspectives is crucial for addressing concerns and fostering trust in AI-driven healthcare solutions.

Purpose of the Study:

• To examine patient knowledge, attitudes, and perceived barriers regarding the use of AI in radiology within the United Arab Emirates (UAE).
• To identify key factors influencing patient acceptance of AI in radiological imaging.
• To provide insights for patient-centered AI implementation strategies in the UAE healthcare sector.

Main Methods:

• A cross-sectional study was conducted with 205 participants undergoing radiological imaging in the UAE.
• Data was collected via a pre-tested online questionnaire assessing knowledge, attitudes, and barriers related to AI in radiology.
• Non-probability sampling (convenience and snowball) was utilized, with data analyzed for frequencies and percentages.

Main Results:

• A high percentage of participants (89.8%) believed AI could improve diagnostic accuracy, and 87.8% recognized its role in prioritizing urgent cases.
• Despite general comfort (81%) with AI technology, significant barriers included concerns about data security (80.5%), AI empathy (82.9%), insufficient information (85.8%), and cost (87.3%).
• Most participants (86.3%) felt AI could enhance radiological service quality, and 83.9% were satisfied with its potential applications.

Conclusions:

• UAE patients generally support AI in radiology, acknowledging its potential benefits for diagnostic accuracy.
• Significant concerns regarding data security, AI empathy, and understanding of the technology were identified.
• Addressing these concerns through enhanced patient education, transparent communication, and robust regulatory frameworks is essential for fostering trust and acceptance of AI in radiology.