Automated AI system for assessing kidney transplant health
Official title: BANFF-AID: Banff Automated Nephrology Feature Framework - Artificial Intelligence Diagnosis
Funded at Kitware, INC. · NIH-11006066 · Data updated 2026-11-12
This study is testing a new AI tool that helps doctors better check the health of kidney transplants by automatically scoring important tests, making it easier to keep good organs from being thrown away, and it's designed to be user-friendly for the doctors who use it.
Quick facts
| Grant type | Sbir 1 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Kitware, INC. NIH-funded |
| Lab location | 1 site (Clifton Park, United States) |
| Project start | September 4, 2024 |
| Project end | August 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $306,873 |
| NIH project number | 1R43DK141305-01 |
| Project ID | NIH-11006066 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals awaiting kidney transplants or those involved in kidney transplantation processes.
✕Less likely to help
Patients who are not candidates for kidney transplantation or those with non-renal conditions may not receive any benefit from this research.
What this research studies
This research focuses on improving the evaluation of kidney transplant health by using an artificial intelligence (AI) system to automate the scoring of Banff Lesion Scores, which are critical for assessing allografts. The project aims to reduce variability in human assessments that can lead to the unnecessary discarding of viable donor organs. By developing a user-friendly web-based platform, the AI will analyze biopsy slides and provide accurate, continuous scoring, while allowing pathologists to make corrections when necessary. This innovative approach seeks to enhance the efficiency and reliability of kidney transplant evaluations.
Why it matters
Potential benefit: If successful, this research could lead to better preservation of viable donor kidneys, ultimately improving transplant outcomes for patients.
How similar studies have gone: Other research has shown promise in using AI for medical diagnostics, indicating that this approach could lead to significant advancements in kidney transplant evaluations.
Where this research is happening
-
Kitware, INC.
Clifton Park, United States Active
Researchers
- Principal investigator: Chaudhary, Aashish — Kitware, INC.
- Study coordinator: Chaudhary, Aashish
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.