From hype to help: delivering real-world clinical value from AI in imaging
Artificial intelligence (AI) is now widely available in clinical imaging, yet its adoption into routine practice has been uneven. This article examines why regulatory clearance alone is insufficient to ensure clinical value and explores the practical considerations required for responsible AI deployment in radiology. Key themes include clinical risk assessment, local validation, explainability, workflow integration and multidisciplinary governance.
Drawing on real-world experience, the article highlights how trust, usability, and standards-based interoperability influence adoption among radiologists, radiographers and medical physicists. The discussion concludes by outlining emerging trends in collaborative and agentic AI systems, emphasising the importance of aligning innovation with patient safety, clinical oversight and long-term service sustainability.
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