Imaging and EHR data combine to predict ICU outcomes with clinician and patient input
Official title: Co-Design and Collaborative Development of an Imaging-Text-EHR Multimodal Foundation Model for Outcome Prediction of Critically Ill Patients
Funded at University of California, San Diego · NIH-11538923 · Data updated 2026-11-12
Aims to build a computer model that uses chest X-ray images, doctor notes, and electronic health record data to predict outcomes for ICU patients, with input from clinicians, patients’ families, and ethics experts.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Diego NIH-funded |
| Lab location | 1 site (La Jolla, United States) |
| Project start | June 30, 2025 |
| Project end | June 29, 2027 |
| Funding year | 2026 |
| Award (this year) | $818,681 |
| NIH project number | 3OT2OD037995-01S1 |
| Project ID | NIH-11538923 on NIH RePORTER |
Who could benefit from this research
✓Could help
ICU patients whose care involves chest X-rays, clinical notes, and EHR data, and who may benefit from informed decision making.
✕Less likely to help
Patients whose data cannot be used due to privacy restrictions or whose care contexts do not involve ICU risk or multimodal prediction.
What this research studies
This project will bring together chest X-rays, clinical notes, and structured health data to create a multimodal foundation model. The team will co-design the system with clinicians, family members, ethics experts, and computer scientists to ensure the tool is trustworthy and useful at the bedside. The model will be refined to predict mortality and morbidities at multiple time points (e.g., 4, 12, 24, 48 hours) and provide explanations for its predictions to support clinical decision making.
Why it matters
Potential benefit: If successful, clinicians could identify high-risk ICU patients earlier and tailor care plans more effectively.
How similar studies have gone: Prior multimodal models using imaging and EHR data have shown promise, but this project emphasizes co-design with stakeholders to improve real-world use.
Where this research is happening
-
University of California, San Diego
La Jolla, United States Active
Researchers
- Principal investigator: Gabriel, Rodney Allanigue — University of California, San Diego
- Study coordinator: Gabriel, Rodney Allanigue
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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.