
AI models combining mammography and clinical data improve identification of women at high short-term breast cancer risk.
Key Details
- 1Researchers combined clinical information with mammogram data in risk assessment models.
- 2The study used data from over 2,000 women screened for breast cancer between 2013 and 2020.
- 3418 women developed breast cancer within two years; 1,775 remained cancer-free for at least two years.
- 4Traditional risk models focus on the long-term (5–10 years), but new AI models target short-term (2-year) prediction.
- 5Short-term models can enable more targeted screening and earlier, less invasive intervention.
Why It Matters
Enhancing short-term risk prediction can help personalize breast cancer screening, potentially leading to earlier detection and better outcomes. AI-driven approaches could shift screening practices towards more individualized and timely care.

Source
Health Imaging
Related News

•Radiology Business
Rayus Radiology Launches $40 AI Mammography Screenings in Washington
Rayus Radiology is introducing a $40 AI-enhanced mammography add-on service at clinics in Washington state.

•AuntMinnie
AI Tool Mirai Shows Robust Performance for Interval Breast Cancer Detection
The Mirai AI model significantly improves detection of interval breast cancers in negative screening mammograms.

•Radiology Business
AI Tool Predicts Interval Breast Cancer Risk from Negative Mammograms
AI can predict interval breast cancer risk up to three years after a negative mammogram.