BreastGeneralAI / InformaticsResearch
AI breast cancer risk predictions remain stable over time and enable personalized screening intervals
Radiology (RSNA)Jun 1
AI-based 2-year breast cancer risk scores were stable for most women across consecutive mammograms, with a mean absolute change of just 0.006. For the 3.5% with a large score increase, short-term cancer incidence was 3.5-fold higher, supporting use of AI to guide personalized re…
- Retrospective cohort of 53,858 women with two consecutive screening mammograms analyzed with a validated deep-learning model; mean interval between exams was 2.1 years.
- Large AI risk-score increases (>0.20) occurred in only 3.5% of women but were associated with a 3.5-fold higher 2-year cancer incidence (95% CI 2.8–4.3) compared to women with stable scores.
- Single-institution, retrospective design; generalizability to other populations and AI models requires prospective, multi-site validation.
Also covered by
- <![CDATA[Mammography Study Shows Dynamic Changes of AI Risk Scores Years Before Breast Cancer Diagnosis]]> · Diagnostic Imaging
- AI Risk Prediction’s Long-Term Value · The Imaging Wire
- Longitudinal Analysis of Changes in Deep Learning Image-based Breast Cancer Risk Scores over Time. · Radiology (RSNA)
- AI-generated risk scores help predict future breast cancer cases · Radiology Business
Automated summary
RadPigeon summaries are original and for information only. They are not clinical advice.