In a recently published study by Amandeep Minhas, Subhash Chandra Pal, and Karan Jain from Scientific Reports, researchers applied machine learning to integrate blood pressure and pulse signals for early CAD detection. By employing an integrated fusion module along with classifiers like neural networks, they achieved nearly 90% accuracy. This approach represents a promising non-invasive screening tool for cardiovascular health, offering an actionable model for further validation in clinical settings.