Understanding how biased algorithms affect cancer surveillance for survivors
Personalized Risk-AdaptIve Surveillance (PRAISE) - Implications of Algorithmic Bias
This study is looking at how technology can help keep an eye on colorectal cancer survivors by predicting who might be at higher risk of their cancer coming back, so they can get the right check-ups and support, while also making sure that everyone gets fair treatment regardless of their background.
Quick facts
| Grant type | R37 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Washington NIH-funded |
| Lab location | 1 site (Seattle, United States) |
| Project ID | NIH-10932845 on NIH RePORTER |
What this research studies
This research investigates the impact of algorithmic bias on the surveillance of colorectal cancer survivors. It aims to develop a personalized risk-adaptive surveillance framework that uses machine learning to predict the risk of cancer recurrence. By identifying high-risk patients, the study seeks to improve the frequency and effectiveness of surveillance testing. The research also addresses how biases in data can lead to disparities in patient outcomes, ensuring that all patients receive equitable care.
Who could benefit from this research
Good fit: Ideal candidates for this research are colorectal cancer survivors who are currently under surveillance for recurrence.
Not a fit: Patients who have not been diagnosed with colorectal cancer or are not currently undergoing surveillance for recurrence may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and equitable surveillance strategies for colorectal cancer survivors, improving their chances of early detection and better outcomes.
How similar studies have performed: Previous research has shown that addressing algorithmic bias can lead to improved health outcomes, suggesting that this approach has the potential for significant impact.
Where this research is happening
Seattle, United States
- University of Washington — Seattle, United States (Active)
Researchers
- Principal investigator: Bansal, Aasthaa — University of Washington
- Study coordinator: Bansal, Aasthaa
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.