UK patients invited to decide on AI use in X-ray analysis, study led by Dr. Maya Jafari

UK researchers, led by Dr. Maya Jafari, launch surveys to gauge patient consent for AI-assisted X-ray analysis, seeking safer, ethical, and transparent NHS use.

A Middlesbrough-based clinician is steering a UK-wide study to gauge whether patients want details about how artificial intelligence helps interpret hospital X-rays. The online survey seeks public input on AI's role in radiology and how information is shared. The goal is clearer, safer, and more transparent NHS use of AI.

Dr. Maya Jafari from James Cook University Hospital explains that AI currently analyzes around 60 to 100 chest X-rays each day, flagging cases with potential problems to help prioritise investigations. Clinicians still review every image, with AI acting as a second pair of eyes.

To raise patient awareness, the team suggests simple information, such as leaflets in waiting rooms, while maintaining professional oversight and safety checks. The IMPACT-AI survey, launched in October, is open to anyone aged 16 and over in the UK and takes only a few minutes to complete; it closes at the end of January.

A separate survey for health professionals asks how AI is used to read scans, what decisions are informed by the software, and what safety checks are in place. The researchers hope these two surveys will give the NHS a clear roadmap for integrating AI in a way that benefits patients and staff alike.

Key Takeaways

Patients will decide whether they want information about AI use in X-ray analysis.
AI helps flag potentially serious chest X-rays, speeding up triage while clinicians review images.
Transparency and safety checks are central to ethical AI adoption in radiology.
Two UK-wide surveys are underway: one for the public (over 16) and one for health professionals.
The findings aim to guide a practical NHS roadmap for safe AI use in everyday care.

Expert comment: AI can speed up triage and improve detection, but transparent patient information is essential for trust. Ongoing feedback will help shape responsible NHS AI guidelines.

In short, the study explores how AI can speed up radiology while preserving patient rights. It seeks clear information flows, consent, and governance to ensure safe, ethical use. By gathering perspectives from the public and clinicians, the NHS could gain a practical roadmap for AI deployment in everyday care. The results may influence how clinics communicate AI involvement and safety checks in X-ray services across the country.