Patient Perceptions of the Use of Artificial Intelligence in Radiology: A Scoping Review.

Journal: Academic radiology
Published Date: Jan 19, 2026

Abstract

INTRODUCTION: Artificial intelligence (AI) is increasingly being used to support diagnostic accuracy and efficiency in radiology. While its technical potential is well recognized, little is known about how patients perceive these tools or whether their expectations align with clinical adoption. We aimed to synthesize literature capturing patient perceptions of the use of AI in radiology. METHODS: This was a scoping review of empirical literature that has explored patient perceptions of AI in radiology. We conducted a comprehensive search across Medline, Embase and Google Scholar for studies published before December 2025. Eligible studies focused on patient views regarding AI in any radiologic context. Data were synthesized using descriptive and thematic analysis. RESULTS: Out of 5284 abstracts screened, 18 studies were included, representing 11 countries and 6574 patients. Six key themes emerged: (i) Trust and confidence in AI, (ii) Need for human oversight, (iii) Understanding and literacy, (iv) Emotional reactions to AI, (v) Accountability, and (vi) Expectations from AI. Patients expressed cautious interest in AI applications but emphasized the need for radiologist involvement. They also showed a preference for using AI as a supportive tool rather than as a replacement for clinicians. CONCLUSION: Patients are central to the integration of AI in radiology, yet literature examining patient perceptions of the use of AI in radiology is scarce. In the era of AI-driven technology, understanding and incorporating patient views is essential to the successful and ethical implementation of AI in radiology.

Authors

  • Shreya Udupa
    Faculty of Medicine & Health Sciences, McGill University, Montreal, QC, Canada (S.U., O.S.). Electronic address: [email protected].
  • Ojasvi Sharma
    University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK.
  • Sonali Sharma
    School of Food Science Washington State University Pullman Washington USA.
  • Charlotte J Yong-Hing
    Department of Radiology, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Department of Diagnostic Imaging, BC Cancer, Vancouver, British Columbia, Canada. Electronic address: [email protected].

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