AI-powered CKD risk predictor and care tool
Official title: Artificial Intelligence-based & Ethically-focused Multi-Modal Data Integration Framework for Screening, Diagnosing, and Caring for CKD Patients
Funded at University of Florida · NIH-11556752 · Data updated 2026-11-12
A cloud-based AI tool will combine medical records, images, and pathology data to predict a patient’s 5-year CKD risk and highlight modifiable factors to guide care.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Florida NIH-funded |
| Lab location | 1 site (Gainesville, United States) |
| Project start | September 1, 2025 |
| Project end | August 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $1,962,384 |
| NIH project number | 3OT2OD038014-01S1 |
| Project ID | NIH-11556752 on NIH RePORTER |
Who could benefit from this research
✓Could help
Adults with chronic kidney disease who have or will generate data across EHR, imaging, and pathology datasets may be eligible.
✕Less likely to help
Patients with CKD for whom comprehensive multi-modal data are not available or usable by the AI system may receive limited or no benefit.
What this research studies
If you have chronic kidney disease, this project aims to build an AI system that uses your health records, lab results, radiology images, and pathology slides to forecast how your kidney disease might progress over five years. The tool will break down large pathology images into many small parts to learn from detailed tissue patterns and combine this with other data types for accurate predictions. It is designed to assist primary care doctors and nephrologists in prioritizing treatments and helping patients focus on the most impactful risk factors. The ultimate goal is to provide personalized risk profiles that support timely, informed decisions about managing CKD.
Why it matters
Potential benefit: If successful, patients could receive more precise risk estimates and personalized guidance to reduce progression and complications.
How similar studies have gone: Related efforts show promise for multi-modal AI in healthcare, but applying it specifically to CKD progression with histopathology is an emerging approach.
Where this research is happening
-
University of Florida
Gainesville, United States Active
Researchers
- Principal investigator: Sarder, Pinaki — University of Florida
- Study coordinator: Sarder, Pinaki
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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.