This research investigates the importance of postdeployment monitoring for AI systems in radiology.
Review of current guidelines for AI implementation in radiology
Analysis of postdeployment monitoring practices
Evaluation of safety measures in AI integration
Postdeployment monitoring is critical for ensuring the safety of AI systems in clinical settings
Guidelines suggest ongoing assessment as part of the total product life cycle
AI implementation requires standardized monitoring protocols for effective safety management
Abstract
Radiology is increasingly adopting AI systems, and to ensure their safety after the systems go live, postdeployment monitoring is essential as part of the total product life cycle framework.