Designing AI tools to help diagnose brain tumors in children
Official title: Human-centered design of clinical AI to support the diagnosis of pediatric suprasellar tumors
Funded at University of Colorado Denver · NIH-10929996 · Data updated 2026-11-12
This study is working on smart computer tools to help doctors better diagnose brain tumors in children, making sure these tools fit nicely into their daily work and provide the right information when they need it.
Quick facts
| Grant type | Fellowship grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Colorado Denver NIH-funded |
| Lab location | 1 site (Aurora, UNITED STATES) |
| Project start | July 3, 2023 |
| Project end | July 2, 2026 |
| Funding year | 2024 |
| Award (this year) | $37,574 |
| NIH project number | 5F31CA275272-02 |
| Project ID | NIH-10929996 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are children diagnosed with suprasellar tumors or those at risk for such conditions.
✕Less likely to help
Patients with brain tumors other than suprasellar tumors may not benefit directly from this research.
What this research studies
This research focuses on creating artificial intelligence (AI) tools to assist doctors in diagnosing pediatric suprasellar tumors, which are a type of brain tumor. By employing a human-centered design approach, the project aims to ensure that these AI tools meet the specific needs of clinicians and integrate seamlessly into their workflows. The research involves collaboration among experts in clinical medicine, AI, and social sciences to develop effective solutions. The goal is to enhance decision-making in pediatric neuro-oncology by providing timely and relevant information to healthcare providers.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and timely diagnoses of pediatric brain tumors, improving treatment outcomes for affected children.
How similar studies have gone: While AI applications in clinical settings have had limited success, recent advancements in AI technology suggest potential for breakthroughs in similar research areas.
Where this research is happening
-
University of Colorado Denver
Aurora, United States Active
Researchers
- Principal investigator: Prince, Eric W — University of Colorado Denver
- Study coordinator: Prince, Eric W
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.