Using ECG and AI to find childhood cancer survivors at risk for late cardiomyopathy
Official title: Early Identification of Childhood Cancer Survivors at High Risk for Late Onset Cardiomyopathy: An Artificial Intelligence Approach utilizing Electrocardiography
Funded at Wake Forest University Health Sciences · NIH-11417087 · Data updated 2026-11-12
This project uses routine ECG tracings plus artificial intelligence to spot childhood cancer survivors who may develop heart muscle disease years later.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Wake Forest University Health Sciences NIH-funded |
| Lab location | 1 site (Winston-Salem, United States) |
| Project start | April 15, 2022 |
| Project end | March 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $38,234 |
| NIH project number | 3R01CA261834-04S1 |
| Project ID | NIH-11417087 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adult survivors of childhood cancer—especially those treated with anthracyclines or chest-directed radiation—who have ECGs and follow-up heart data available.
✕Less likely to help
People who never received cardiotoxic cancer therapy or who already have established cardiomyopathy are less likely to benefit from this predictive ECG tool.
What this research studies
As a childhood cancer survivor, your past treatment with anthracycline chemotherapy or chest radiation can raise your risk for late heart problems. The team will train an AI model on raw ECG recordings linked to long-term heart outcomes so the algorithm can recognize subtle signals that predict future cardiomyopathy. They will build a robust model and then test it across multiple centers and datasets to make sure it works for different groups of survivors. The goal is a tool that could flag people for earlier heart imaging or preventive care before symptoms appear.
Why it matters
Potential benefit: If successful, this tool could let clinicians use a simple ECG to identify survivors who need closer heart monitoring or early treatment to prevent worsening heart function.
How similar studies have gone: Earlier work in the St. Jude Lifetime Cohort showed promising accuracy (AUC ~0.87) using AI on ECGs, but broader multi-center validation is still needed.
Where this research is happening
-
Wake Forest University Health Sciences
Winston-Salem, United States Active
Researchers
- Principal investigator: Akbilgic, Oguz — Wake Forest University Health Sciences
- Study coordinator: Akbilgic, Oguz
Related research
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Identifying childhood cancer survivors at risk for heart problems using AI and ECG data.
This study is working on a smart computer program that looks at heart test results to help find childhood cancer survivors who might be at risk for heart problems later on, so they can get the care they need to stay healthy.
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Strategies to Find and Reconnect Adolescent and Young Adult Cancer Survivors to Adult Follow-Up Care
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Digital self-management and peer mentoring to help childhood cancer survivors transition to adult care
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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.