Improving quality assurance in radiation therapy using AI tools
Development of AI-Augmented quality assurance tools for radiation therapy
['FUNDING_R01'] · STANFORD UNIVERSITY · NIH-11014970
This study is working on using smart computer tools to make sure that radiation therapy for cancer is done safely and accurately, so patients can feel confident they are getting the best treatment possible.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | STANFORD UNIVERSITY (nih funded) |
| Locations | 1 site (STANFORD, UNITED STATES) |
| Trial ID | NIH-11014970 on ClinicalTrials.gov |
What this research studies
This research focuses on enhancing the quality assurance (QA) processes in radiation therapy by developing advanced AI-augmented tools. It aims to address current limitations in QA methods, which can be labor-intensive and costly, by leveraging deep learning techniques. The project will create a framework to verify treatment machine parameters and dose delivery, ensuring that patients receive accurate and effective radiation treatment. By integrating AI into the QA workflow, the research seeks to improve the reliability and efficiency of radiation therapy.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients undergoing radiation therapy for cancer treatment.
Not a fit: Patients who are not receiving radiation therapy or those with conditions that do not require such treatment may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to safer and more effective radiation therapy treatments for patients.
How similar studies have performed: Other research has shown promising results in using AI for medical applications, indicating potential success for this innovative approach.
Where this research is happening
STANFORD, UNITED STATES
- STANFORD UNIVERSITY — STANFORD, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: XING, LEI — STANFORD UNIVERSITY
- Study coordinator: XING, LEI
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 below.