Certified Cancer Registry Extraction with Proof-Certified Trust
Official title: SCH: Proof-Certified Cancer Registry Extraction
Funded at Arizona State University-Tempe Campus · NIH-11579067 · Data updated 2026-11-12
A new AI-powered system helps cancer registries extract standardized data from medical records more accurately and with formal proofs to ensure trust.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Arizona State University-Tempe Campus NIH-funded |
| Lab location | 1 site (Scottsdale, United States) |
| Project start | September 1, 2026 |
| Project end | August 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $300,000 |
| NIH project number | 1R01CA323939-01 |
| Project ID | NIH-11579067 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients whose cancer care data may be included in registries and who contribute to medical records used for registry extraction.
✕Less likely to help
Patients whose data are not included in registries or who are not part of contributing EHRs may not directly benefit.
What this research studies
This project develops a fusion of AI and formal reasoning to extract registry data from oncology notes, pathology reports, and imaging summaries. It creates a typed language and a clinical proof kernel to certify each data claim before it can be used for reporting or quality improvement. The approach includes training models that propose values along with supporting evidence and proofs, while uncertain cases are explained and escalated for review. The goal is a registry-grade data extraction framework that can be audited and governed, improving accuracy and trust in cancer surveillance data.
Why it matters
Potential benefit: If successful, it could make cancer registry data more accurate and auditable, supporting better surveillance and research.
How similar studies have gone: Previous AI approaches lacked formal verification for registry-grade data; this project aims to add certified credibility to automated extractions.
Where this research is happening
-
Arizona State University-Tempe Campus
Scottsdale, United States Active
Researchers
- Principal investigator: Zhou, Xuanyu — Arizona State University-Tempe Campus
- Study coordinator: Zhou, Xuanyu
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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.