The implementation of artificial intelligence in radiology: a narrative review of patient perspectives

Abstract

Aim: To synthesise research on the view of the public and patients of the use of artificial intelligence (AI) in radiology investigations.

Methods: A literature review of narrative synthesis of qualitative and quantitative studies that reported views of the public and patients toward the use of AI in radiology.

Results: Only seven studies related to patient and public views were retrieved, suggesting that this is an underexplored area of research. Two broad themes, of confidence in the capabilities of AI, and the accountability and transparency of AI, were identified.

Conclusions: Both optimism and concerns were expressed by participants. Transparency in the implementation of AI, scientific validation, clear regulation and accountability were expected. Combined human and AI interpretation of imaging was strongly favoured over AI acting autonomously. The review highlights the limited engagement of the public in the adoption of AI in a radiology setting. Successful implementation of AI in this field will require demonstrating not only adequate accuracy of the technology, but also its acceptance by patients.

Keywords: artificial intelligence; machine learning; patient perspective; radiology.