Engineering Your Heart’s Health

Imagine a virtual model that mirrors a patient’s heart and updates itself as new health and environmental information emerges. By combining medical data with biophysical knowledge, this model can simulate how the heart functions, anticipate how disease may progress, and predict how a patient might respond to treatment. These personalized, evolving replicas—known as digital twins—provide clinicians with a powerful tool for early risk assessment and more informed decisions. This lecture examines how machine learning and physics-based heart models are converging to advance precision care in cardiology. Speakers

• Natalia Trayanova, Professor of Medicine at the Johns Hopkins School of Medicine