Using AI to predict how trauma patients respond to resuscitation
R01 Administrative Supplement for AI Prediction of Trauma Resuscitation Responsiveness
This study is looking at how artificial intelligence can help doctors give better and faster treatment to trauma patients with severe bleeding, so they can quickly figure out who needs the most help and provide the right care to save lives.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California at Davis NIH-funded |
| Lab location | 1 site (Davis, United States) |
| Project ID | NIH-10908960 on NIH RePORTER |
What this research studies
This research investigates how artificial intelligence can improve the initial treatment of trauma patients who are experiencing severe bleeding. By analyzing the unique responses of individual patients to injury, the project aims to develop better decision-making tools for healthcare providers at the bedside. The goal is to identify patients at risk of poor outcomes more quickly and tailor resuscitation efforts to their specific needs, potentially saving lives in critical situations.
Who could benefit from this research
Good fit: Ideal candidates for this research are trauma patients who are experiencing significant blood loss and require immediate medical intervention.
Not a fit: Patients who are not experiencing trauma or those with stable conditions unrelated to bleeding may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatment strategies for trauma patients, reducing preventable deaths from hemorrhage.
How similar studies have performed: Other research has shown promise in using AI for medical decision-making, indicating that this approach could lead to significant advancements in trauma care.
Where this research is happening
Davis, United States
- University of California at Davis — Davis, United States (Active)
Researchers
- Principal investigator: Callcut, Rachael a — University of California at Davis
- Study coordinator: Callcut, Rachael a
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.