Radiology AI literacy, Part II: How to interpret and troubleshoot AI results at the workstation

A foundational primer explains how radiology AI tools process images, present results, and integrate with workflows. Misalignments at the radiologist-AI interface can create cognitive burdens and diminish the efficiency gains promised by marketed solutions. Understanding the int…

• Part II of an educational primer series building AI literacy for practicing radiologists, covering the radiologist-AI interface, result availability, and workflow alignment.
• Addresses practical end-user questions: intended use, the process from image input to AI output, and why results may be absent at the time of interpretation.
• Discusses emerging medicolegal considerations for storing AI results and optimizing the presentation of AI outputs.

Automated summary

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