A deep learning model can predict cardiovascular risk in women using routine mammograms, performing comparably to traditional risk calculators.
Key Details
- 1Developed by The George Institute for Global Health in collaboration with UNSW and University of Sydney.
- 2Uses only mammographic features and age—no need for additional clinical data.
- 3Validated using data from over 49,000 routine mammograms linked to hospital and death records.
- 4Performs comparably to traditional cardiovascular risk models requiring more extensive data.
- 5Potential for integration into existing high-participation breast screening programs globally.
Why It Matters
This approach could allow opportunistic cardiovascular risk screening for women already undergoing mammograms, potentially improving early identification and prevention of heart disease. It demonstrates innovative use of imaging AI beyond traditional cancer detection, with public health implications for women's care.
Source
EurekAlert
Related News
•EurekAlert
FDA Approves Johns Hopkins AI Tool for Early Sepsis Detection
FDA clears an AI-driven system developed by Johns Hopkins to detect sepsis up to 48 hours earlier and reduce mortality rates.
•EurekAlert
New AI Vision-Language Model Enhances Chest CT Diagnostics
Researchers developed an interpretable AI model that uses visual question answering to generate detailed diagnostic findings from chest CT scans, aimed at improving lung cancer diagnosis.
•EurekAlert
Optical AI Chip Boosts Real-Time Dry Eye Gland Diagnosis Accuracy
A new metasurface spectral AI chip enables rapid, accurate diagnosis of meibomian gland dysfunction (MGD) from tissue samples, achieving 96.22% accuracy.