Oversight May Be Critical in Patient Acceptance of AI in Radiology
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By
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Andrea Surnit
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July 14, 2026
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3 min
Clinical Report: Oversight May Be Critical in Patient Acceptance of AI in Radiology
Overview
A study involving 162 patients revealed that while most view AI as beneficial in healthcare, there is significant opposition to autonomous decision-making without physician oversight. The findings indicate a strong preference for maintaining the clinician-patient relationship alongside AI integration.
Background
The integration of artificial intelligence (AI) in healthcare, particularly in radiology, is rapidly advancing. Understanding patient attitudes toward AI is crucial as it can influence the acceptance and implementation of these technologies in clinical settings.
Data Highlights
| Finding | Percentage |
|---|---|
| Believed AI would be useful in healthcare | 78% |
| Supported the use of AI in healthcare | 64% |
| Preferred physician responsibility for AI decisions | 71% |
| Believed AI could reduce healthcare waiting times | 70% |
| Would want to know if AI predicted future disease | 77% |
| Did not trust a computer to make medical decisions | 50% |
| Did not believe AI could replace physicians | 70% |
| Considered it important to be treated as a person | 93% |
| Would not be satisfied with AI decisions ignoring feelings | 80% |
Key Findings
- 78% of respondents believed AI would be useful in healthcare.
- 64% supported the use of AI in healthcare.
- 71% believed physicians should remain responsible for AI-related decisions.
- 93% considered it important to be treated as a person rather than a number.
- 70% did not believe AI could replace physicians.
- 50% did not trust a computer to make medical decisions.
Clinical Implications
The study found that while patients are open to the integration of AI in radiology, they prefer that physicians remain involved in decision-making processes.
Conclusion
The findings indicate a preference for physician involvement in AI-assisted decision-making.
Related Resources & Content
- Maclean RH, Goh V, British Journal of Radiology, 2024 -- Oversight May Be Critical in Patient Acceptance of AI in Radiology
- Journal of Medical Internet Research (JMIR) — Patients’ Perspectives on the Implementation of AI in Radiological Diagnostics: Focus Group Study
- European Radiology — A Comprehensive Guide to the Role of Artificial Intelligence in Thoracic Imaging: Insights from the European Society of Thoracic Imaging (ESTI)
- Frontiers in Digital Health — Implementing AI innovation in radiology departments in the English NHS: a qualitative study on the experiences of professionals, patient groups and innovators
- European Radiology — Guiding Radiology Through Technological Innovation and the Rise of Artificial Intelligence
- Patients’ Perspectives on the Implementation of AI in Radiological Diagnostics: Focus Group Study
- A Comprehensive Guide to the Role of Artificial Intelligence in Thoracic Imaging: Insights from the European Society of Thoracic Imaging (ESTI)
- Implementing AI innovation in radiology departments in the English NHS: a qualitative study on the experiences of professionals, patient groups and innovators
- Full Document Preview
- https://www.rsna.org/-/media/files/rsna/media/artificial-intelligence-in-radiology.pdf?hash=4BEEBED94BE89D564645B09D3E420738&rev=f145cec260b94b07abdd4f533fbf1d4b
- Transparency for Machine Learning-Enabled Medical Devices: Guiding Principles | FDA
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- Article 14: Human oversight | AI Act Service Desk
- Best Practices for the Safe Use of Large Language Models and Other Generative AI in Radiology | Radiology
- AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial | Nature Medicine
- Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study - ScienceDirect
- Patient Perceptions of the Use of Artificial Intelligence in Radiology: A Scoping Review - ScienceDirect
- Journal of Medical Internet Research - Patients’ Perspectives on the Implementation of AI in Radiological Diagnostics: Focus Group Study
- https://www.rsna.org/media/press/i/2572?PdfExport=1
- Ethical Obligations to Inform Patients About Use of AI Tools
This content is an AI-generated, fully rewritten summary based on a published scholarly article. It does not reproduce the original text and is not a substitute for the original publication. Readers are encouraged to consult the source for full context, data, and methodology.
