A deep learning AI model based on mammographic features can predict cardiovascular risk in women with accuracy comparable to traditional risk scores.
Key Details
- 1Researchers from the George Institute for Global Health developed a deep-learning algorithm using mammogram images and patient age.
- 2The model was trained on 49,196 women with a median follow-up of 8.8 years, 3,392 of whom experienced a major cardiovascular event.
- 3The AI algorithm (DeepSurv) achieved a concordance index of 0.72; traditional risk models range from 0.73 to 0.79.
- 4Combining mammogram radiomics with clinical data increased the concordance index to 0.75.
- 5The model is designed for integration into routine breast cancer screening to provide additional cardiovascular risk information.
Why It Matters
This work demonstrates the potential for mammography-based AI to serve as a dual-purpose screening tool, improving both cancer and cardiovascular disease prevention in women by leveraging existing imaging data. If implemented, it could enhance patient care without adding screening burden or workload.

Source
AuntMinnie
Related News

•Radiology Business
Radiologists Prefer Domain-Specific AI for CT Report Generation
Radiologists show a clear preference for domain-specific AI models in generating accurate and timely CT report impressions.

•Radiology Business
GE HealthCare and RadNet Expand Global AI Mammography Partnership
GE HealthCare and RadNet are extending their partnership globally to offer AI-enhanced mammography systems.

•HealthExec
UT Austin to Launch $1B+ AI-Driven Medical Center With Major Gift
UT Austin receives $750 million from Michael and Susan Dell toward a $1 billion+ AI-native medical center opening in 2030.