An AI model accurately predicted breast cancer risk in a racially and ethnically diverse screening population using mammogram data.
Key Details
- 1Study included 206,929 women (average age 56.1) from a province-wide screening program starting at age 40.
- 2AI model used both current and up to four years of prior mammograms for risk scoring.
- 3Model achieved AUROC of 0.78 overall, 0.77 in East Asian, 0.77 in Indigenous, and 0.75 in South Asian women.
- 44,168 breast cancer cases confirmed over an average 5.3-year follow-up.
- 5Model showed consistent performance across age groups and ethnicities.
Why It Matters
Demonstrating robust, consistent AI performance across diverse populations supports its broader clinical adoption. Such risk models may enable more personalized and equitable breast cancer screening and resource allocation.
Source
AuntMinnie
Related News
•AuntMinnie
AI Enables Safe 75% Gadolinium Reduction in Breast MRI Without Losing Sensitivity
AI-enhanced breast MRI with a 75% reduced gadolinium dose maintained diagnostic sensitivity comparable to full-dose protocols.
•Cardiovascular Business
Deep Learning AI Model Detects Coronary Microvascular Dysfunction Via ECG
A new AI algorithm rapidly detects coronary microvascular dysfunction using ECGs, with validation incorporating PET imaging.
•AuntMinnie
Study: Patients Prefer AI in Radiology as Assistive, Not Standalone Tool
Survey finds patients support AI-assisted radiology but not AI-only interpretations.