Evaluating the Performance and Clinical Utility of AI-driven Diagnostic Tools in Radiology

This article provides a practical guide for rigorously evaluating artificial intelligence–driven diagnostic tools in radiology, emphasizing essential statistical methods, testing processes, common pitfalls, and real-world clinical applicability to ensure accurate, reliable, and meaningful integration into clinical practice.