AI-supported heart failure diagnosis and management in Rwanda
Official title: Implementing AI-supported training to scale quality diagnosis and management of heart failure in Rwanda
Funded at Boston Medical Center · NIH-11625877 · Data updated 2026-11-12
Aiming to help people with suspected heart failure in Rwanda get faster, more accurate diagnoses and better care using AI-guided ultrasound and care protocols.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Boston Medical Center NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | September 3, 2026 |
| Project end | May 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $13,603 |
| NIH project number | 3R01HL178903-01A1S2 |
| Project ID | NIH-11625877 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults with suspected heart failure in settings where echo capabilities are limited and nurses or clinicians can be trained to use AI-guided, focused ultrasound.
✕Less likely to help
Patients in settings without access to AI-enabled ultrasound or those not receiving heart failure care could see limited benefit.
What this research studies
This project tests an AI-enhanced, focused ultrasound approach for non-expert clinicians to diagnose and manage heart failure in Rwanda, with the goal of reducing dependence on scarce cardiology experts. After short training, nurses can acquire images, interpret them with AI guidance, and start guideline-based treatment with higher accuracy. The study will compare the AI-augmented workflow to existing training to see if diagnostic accuracy improves and trainer time decreases. It follows a real-world implementation plan in collaboration with Rwanda's Ministry of Health. The EPIS framework will guide exploration, preparation, implementation, and sustainment of the AI-enhanced protocol.
Why it matters
Potential benefit: If successful, patients in rural Rwanda could receive faster, more accurate heart failure care with less need for expert trainers.
How similar studies have gone: Early work in AI-assisted point-of-care ultrasound suggests improved image quality and diagnostic accuracy, but broader, scalable results in LIC settings are still emerging.
Where this research is happening
-
Boston Medical Center
Boston, United States Active
Researchers
- Principal investigator: Kwan, Gene Fazil — Boston Medical Center
- Study coordinator: Kwan, Gene Fazil
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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.