A Heart That Outlives Disease

Cardiovascular disease still kills more people than any other condition on earth, and the field’s standard tools — a handful of risk scores and a small set of drug classes — were designed for a different century. The Cardiac Institute reasons across electrophysiology, vascular biology, hemodynamics, and emerging device science using physics-informed neural networks and digital-twin heart models. It evaluates artificialheart and assist-device architectures, tracks regenerative-cardiology candidates, and builds patient-specific risk trajectories from multimodal imaging and longitudinal biomarkers. Federated learning lets it learn from hospitals and registries without moving the underlying data. Every recommendation is paired with a falsifiable mechanism, a device-engineering assessment, and a regulator-ready credibility plan.

Value proposition:

• Digital-twin hearts for patient-specific decisions
• Device-and-biology reasoning under one roof
• Federated learning, no raw data movement