User Feedback on AI Integration in Diagnostic Imaging Devices
Methodology
Type of Study
Sample Size
Sample Size
Industry
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Target Audience
the challenge
AI is becoming a major player in diagnostic imaging, promising speed, precision, and support in clinical decisions. But the tech is only as strong as its adoption.
The key challenge: Do radiologists actually trust and value AI integration in their day-to-day work?
Our Approach
We conducted a quantitative CAWI study with 500 radiologists across the USA, gathering their feedback on usability, reliability, and perceived impact of AI-powered imaging tools.
Key Insights
Radiologists see potential in AI for reducing reporting time and highlighting anomalies—automation’s but full trust isn't there yet.
Concerns around over-reliance, interpretability, and workflow disruption persist. What radiologists want is control, transparency, and support—not automation for sake.
Impact
Device manufacturers are now refining how AI fits into radiologist workflows—offering tools that support, not replace, clinical judgment. Clearer reporting interfaces and user-customizable AI features are gaining traction.
Conclusion
AI won’t replace radiologists—but radiologists who use AI well will shape the future of diagnostic accuracy.