Improving kidney transplant decisions using artificial intelligence
Optimizing Preimplantation Kidney Transplant Biopsy Interpretation with Artificial Intelligence Assistance - Resubmission - 1
This study is working on using smart computer technology to help doctors better understand kidney biopsy results, so more kidneys from donors can be safely used for transplants, which could save lives and help patients waiting for a transplant.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | New York University School of Medicine NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-10980817 on NIH RePORTER |
What this research studies
This research aims to enhance the interpretation of kidney biopsies before transplantation by utilizing advanced artificial intelligence techniques. Many kidneys from deceased donors are discarded due to uncertain biopsy results, but this project seeks to develop a reliable AI system that can provide accurate interpretations, even when expert pathologists are not available. By analyzing digital images of kidney biopsies, the AI will help identify which kidneys are suitable for transplantation, potentially saving lives and reducing waitlist mortality. The goal is to ensure that more usable kidneys are successfully transplanted, improving outcomes for patients.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals on the kidney transplant waitlist who may benefit from receiving a kidney from a deceased donor.
Not a fit: Patients who are not on the kidney transplant waitlist or those who are not suitable candidates for kidney transplantation will not benefit from this research.
Why it matters
Potential benefit: If successful, this research could significantly increase the number of viable kidneys available for transplantation, leading to better patient outcomes and reduced mortality rates on the transplant waitlist.
How similar studies have performed: Other research has shown promising results in using AI for medical imaging and pathology, indicating that this approach could be effective in improving kidney transplant outcomes.
Where this research is happening
New York, United States
- New York University School of Medicine — New York, United States (Active)
Researchers
- Principal investigator: Segev, Dorry L. — New York University School of Medicine
- Study coordinator: Segev, Dorry L.
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.