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
•Radiology Business
Real-World Study: Radiology AI Best in Emergency and Inpatient Settings
A commercial AI tool for intracranial aneurysm detection outperformed in inpatient and emergency settings but yielded limited benefits for outpatients in a major health system study.
•Radiology Business
New Rubric Enhances Safety of AI-Generated Radiology Summaries
Researchers developed a five-factor rubric to assess the safety and quality of AI-generated, patient-friendly radiology report summaries.
•Radiology Business
UCLA Review Evaluates Breast AI for Early Cancer Detection
A UCLA-led review analyzes current evidence for AI tools in screening mammography, focusing on their capability to detect interval cancers.