AI and remote interpreters to improve cancer visits for people who speak limited English
Official title: Pilot Project 1: AI Heals (Health Advances Through Language Solutions)?
Funded at City College of New York · NIH-11194449 · Data updated 2026-11-12
This project compares three ways of translating during cancer visits—phone consecutive interpreting, human simultaneous interpreting, and AI-based simultaneous interpreting—for people who speak English less than "very well" to find which has fewer critical errors and faster communication.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | City College of New York NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 26, 2008 |
| Project end | August 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $47,100 |
| NIH project number | 5U54CA132378-17 |
| Project ID | NIH-11194449 on NIH RePORTER |
Who could benefit from this research
✓Could help
People with cancer who speak English less than "very well" and who regularly need interpreter services during oncology visits are the ideal candidates.
✕Less likely to help
Patients who speak English well, do not need interpretation, or whose care is not in oncology are unlikely to benefit directly from this project.
What this research studies
If you have cancer and speak English less than "very well," this project looks at three ways to provide interpretation during clinic visits. The team will create 50 real oncology scripts, translate the patient parts into various languages, and use actors to play patients and English-speaking providers while each interpreting method is used. Researchers will compare error rates that could affect care and the time it takes to communicate. The goal is to identify which approach gives clearer, quicker communication that could help patients and clinicians understand each other better.
Why it matters
Potential benefit: If successful, this work could make cancer clinic conversations safer and easier to understand by providing more accurate and faster interpretation.
How similar studies have gone: Remote consecutive interpreting is commonly used and simultaneous human interpreting has shown promise, but AI simultaneous interpreting in clinical oncology is largely new and has limited prior evidence.
Where this research is happening
-
City College of New York
New York, United States Active
Researchers
- Principal investigator: Riobó, Carlos — City College of New York
- Study coordinator: Riobó, Carlos
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.