Improving computer-aided diagnosis for better cancer detection
Official title: VS-EDGE: Visual-Semantic Explanations for Diagnostic Guidance
Funded at De Paul University · NIH-11040266 · Data updated 2026-11-12
This study is working on improving computer programs that help doctors read medical images, like mammograms, for breast cancer, making them more accurate and easier to understand so that doctors can trust their recommendations.
Quick facts
| Grant type | R15 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | De Paul University NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project start | June 16, 2025 |
| Project end | May 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $406,204 |
| NIH project number | 1R15CA297521-01 |
| Project ID | NIH-11040266 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals undergoing diagnostic imaging for breast cancer or other related conditions.
✕Less likely to help
Patients who are not undergoing imaging for cancer or who do not require diagnostic assistance from CAD systems may not benefit from this research.
What this research studies
This research focuses on enhancing computer-aided diagnosis (CAD) systems to analyze radiological images more effectively, particularly for conditions like breast cancer. By developing a model that combines visual and semantic processing, the project aims to create CAD systems that are not only accurate but also explainable, helping clinicians understand the reasoning behind the technology's recommendations. The goal is to bridge the gap between advanced CAD systems and their practical use in clinical settings, ultimately improving diagnostic accuracy and trust among healthcare providers.
Why it matters
Potential benefit: If successful, this research could lead to more reliable and understandable diagnostic tools, improving early detection and treatment outcomes for patients with cancer.
How similar studies have gone: Previous research has shown promise in developing explainable AI systems for medical diagnostics, indicating that this approach could lead to significant advancements in the field.
Where this research is happening
-
De Paul University
Chicago, United States Active
Researchers
- Principal investigator: Raicu, Daniela Stan — De Paul University
- Study coordinator: Raicu, Daniela Stan
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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.