Researchers at The George Institute for Global Health have developed a machine learning algorithm that analyzes routine mammograms to accurately predict cardiovascular disease (CVD) risk in women. This novel approach leverages imaging data commonly acquired in breast cancer screening for dual diagnostic purposes, potentially enabling earlier intervention for CVD, the leading cause of death among females globally. The model integrates complex imaging features to improve personalized risk stratification.