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Researchers have developed a novel artificial intelligence (AI) tool capable of predicting heart disease risk in women by analyzing routine mammogram images and age, without requiring an extensive personal medical history. This innovative development, reported in the peer-reviewed journal Heart on September 17, 2025, promises a resource-efficient and potentially powerful method for cardiovascular risk screening integrated with breast cancer screening practices commonly engaged in by women worldwide.
Key Findings and Developments
The AI tool was trained and validated on mammographic data from over 49,000 women in Victoria, Australia, cross-referenced with hospital and death records to assess cardiovascular outcomes. The deep learning algorithm utilized mammographic features combined with patient age to estimate cardiovascular risk. This approach demonstrated predictive accuracy comparable to traditional cardiovascular risk equations, which generally require multiple clinical data points and detailed medical histories.
Unlike previous models that focused solely on breast arterial calcification—a mammogram feature linked to cardiovascular risk but with limitations especially in older women—this AI model employs a broader range of mammographic imaging features. This results in a more precise and robust risk prediction. The model’s strength lies in its simplicity and practicality, as it does not depend on additional health information, making it less resource-intensive to implement on a large scale.
Expert Perspectives
Clare Arnott, associate professor and global director of the Cardiovascular Program at The George Institute, highlighted the dual benefits of this approach: “By integrating cardiovascular risk screening with breast screening through the use of mammograms—something many women already engage with at a stage in life when their cardiovascular risk increases—we can identify and potentially prevent two major causes of illness and death at the same time.”
Cardiologist Dr. Jennifer Barraclough, a research fellow at The George Institute, emphasized the potential of the tool to serve diverse populations: “Leveraging an existing risk screening process widely used by women could serve as a cardiovascular risk prediction tool for women in diverse communities across Australia and around the world.” The researchers are currently exploring the tool’s applicability across different population groups and assessing implementation challenges.
Context and Background
Cardiovascular disease (CVD) remains the leading cause of death globally among women, often under-recognized compared to male populations. Traditional risk prediction models, such as the Framingham Risk Score or ASCVD (Atherosclerotic Cardiovascular Disease) calculator, rely heavily on detailed clinical data including cholesterol levels, blood pressure, smoking status, and diabetes history. These models can miss subclinical disease signs and may not be equally accurate across all demographics.
Mammograms, routinely used for breast cancer detection, contain vascular information that has been underutilized for cardiovascular risk assessment. Breast arterial calcification, visible on mammograms, has been associated with increased heart disease risk, but its predictive power alone is limited. This AI-based tool represents a novel use of routinely collected imaging data, blending cancer and cardiovascular screening.
Implications for Public Health
If validated in diverse global populations and integrated into routine clinical practice, this AI tool could revolutionize cardiovascular risk screening in women by enabling earlier detection with minimal added burden. Earlier identification of high-risk patients could lead to timely lifestyle changes, preventive interventions, and potentially reduce cardiovascular events and mortality.
By leveraging a screening modality already familiar and acceptable to many women, the approach could improve screening adherence and reach populations who might not otherwise engage in separate cardiovascular risk assessments. The resource-friendly nature of the tool also has implications for healthcare systems with limited access to comprehensive laboratory testing.
Limitations and Counterarguments
Researchers caution that while the AI model shows promise, further testing in broader and ethnically diverse populations is necessary to confirm accuracy and generalizability. There may also be technological and logistical barriers to adoption in some settings.
Additionally, this AI tool does not replace standard clinical assessments but rather aims to complement them. Physicians should continue to evaluate cardiovascular risk using established methods alongside new technologies. Ethical considerations about data privacy and informed consent for AI use will also need to be addressed.
Practical Takeaways for Readers
Women undergoing routine mammograms may in the future benefit from simultaneous cardiovascular risk assessment without extra tests. This integrated approach could prompt women and healthcare providers to take preventive actions sooner, including diet, exercise, smoking cessation, and medication when appropriate.
Healthcare providers and patients alike should maintain awareness that AI tools are adjuncts—not replacements—for comprehensive medical evaluation. Healthy lifestyle choices remain the cornerstone of cardiovascular disease prevention regardless of AI risk assessments.
Medical Disclaimer: This article is for informational purposes only and should not be considered medical advice. Always consult with qualified healthcare professionals before making any health-related decisions or changes to your treatment plan. The information presented here is based on current research and expert opinions, which may evolve as new evidence emerges.
References
- https://www.theweek.in/wire-updates/national/2025/09/17/lst2-research-ai-heart-disease-risk.html#:~:text=Arnott%20said%2C%20%22Our%20model%20is,%2C%20but%20still%20highly%20accurate.%22
