AI-enhanced echocardiogram to predict heart surgery and heart failure outcomes
Official title: Radiomics approach to engineering an artificial intelligence based echocardiography platform to predict cardiovascular surgery and heart failure outcomes.
Funded at Stanford University · NIH-11252601 · Data updated 2026-11-12
This project builds an AI tool that reads full echocardiogram videos to help predict recovery after heart surgery and future risks for people with heart failure.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project start | January 1, 2022 |
| Project end | December 31, 2026 |
| Funding year | 2026 |
| Award (this year) | $541,116 |
| NIH project number | 5R01HL157235-05 |
| Project ID | NIH-11252601 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with heart failure or those being evaluated for, undergoing, or recovering from cardiovascular surgery who have echocardiogram studies would be the most relevant candidates.
✕Less likely to help
People without heart disease, without echocardiogram images, or whose care does not rely on echo measurements are unlikely to benefit directly.
What this research studies
If I were a patient, researchers would use advanced AI to treat my echocardiogram videos as rich data rather than just simple measurements. They will train the system on many time-resolved echo studies linked to real patient outcomes so the AI can learn which motion and texture patterns matter. The team plans to validate the multi-modal platform by comparing its predictions to actual surgical and heart-failure results. This work is led at Stanford and would use patients' echo images and medical records under privacy protections.
Why it matters
Potential benefit: If successful, the tool could provide earlier and more accurate predictions about who will do well after heart surgery or who faces higher risk from heart failure, helping tailor care.
How similar studies have gone: AI has performed well in many medical imaging tasks and some echo automation exists, but using radiomics on full echo videos to predict surgical and heart-failure outcomes is relatively new.
Where this research is happening
-
Stanford University
Stanford, United States Active
Researchers
- Principal investigator: Hiesinger, William — Stanford University
- Study coordinator: Hiesinger, William
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.