AI-Enabled Infrastructure for Tracking Incidental Findings Across the Care Continuum

Incidental finding follow-up remains fragmented and error-prone in radiology. This RSNA session examines AI-enabled operational infrastructure—using breast imaging as a case example—to improve tracking, communication, and care continuity while reducing administrative burden.

• Educational session (RSNA/YouTube) exploring operational—not purely diagnostic—AI applied to incidental finding lifecycle management, from detection through follow-up.
• Breast imaging is used as the primary case example to illustrate how structured workflows and AI tools can close gaps in tracking and patient communication.
• No primary research data or outcome numbers are presented; this is a framework/conceptual session rather than a clinical trial or diagnostic-accuracy study.

RadPigeon summaries are original and for information only. They are not clinical advice.