AI breast cancer risk prediction: balancing promise and calibration for clinical readiness

A review in JNCI examines AI models for breast cancer risk prediction, focusing on calibration, performance variability, and the steps needed before routine clinical use (exact figures not reported in source).

• Review summarizes current AI-based breast cancer risk prediction tools and their calibration shortcomings.
• No quantitative results or original validation data were extractable from the provided metadata.
• Highlights requirement for external, prospective validation before clinical deployment.

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