Unified and fair multimodal learning for autoimmune diseases
Official title: Unified and fair multimodal representation learning for autoimmune diseases
Funded at Univ of North Carolina Chapel Hill · NIH-11625649 · Data updated 2026-11-12
A patient-friendly AI approach will combine many kinds of health data to improve diagnosis and personalized care for autoimmune diseases, including lupus.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Univ of North Carolina Chapel Hill NIH-funded |
| Lab location | 1 site (Chapel Hill, United States) |
| Project start | September 16, 2024 |
| Project end | September 15, 2027 |
| Funding year | 2026 |
| Award (this year) | $1,600,000 |
| NIH project number | 3OT2OD038045-01S2 |
| Project ID | NIH-11625649 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates include individuals suspected of having autoimmune diseases (e.g., lupus) or those with long diagnostic delays who could benefit from improved, data-driven diagnostic support.
✕Less likely to help
Patients whose data do not align with the model inputs or who do not have autoimmune conditions may not benefit directly.
What this research studies
This project aims to create a single, fair AI model that can integrate electronic health records, omics data, imaging, and other clinical information to help diagnose autoimmune diseases earlier and more accurately. It will handle missing data gracefully and provide transparent results that clinicians and patients can understand. The work focuses on reducing diagnostic delays and addressing health equity issues that disproportionately affect Black and Hispanic women with lupus. Researchers will design the model to account for population imbalances and incorporate debiasing strategies from the start. The initiative ultimately seeks to support personalized disease information and care plans tailored to individual patients.
Why it matters
Potential benefit: If successful, patients could experience earlier, more accurate diagnoses and more personalized treatment pathways.
How similar studies have gone: Previous similar AI approaches have shown promise but often struggle with data integration and equity; this project aims to address those gaps.
Where this research is happening
-
Univ of North Carolina Chapel Hill
Chapel Hill, United States Active
Researchers
- Principal investigator: Sheikh, Saira Z — Univ of North Carolina Chapel Hill
- Study coordinator: Sheikh, Saira Z
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Regulation of B cell Responses in SLE and Other Autoimmune Diseases
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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.