Collaborative AI for safer, faster bacteremia care
Official title: SCH: Collaborative and Grounded Al Agents for Accountable Bacteremia Decision
Funded at University of Central Florida · NIH-11579169 · Data updated 2026-11-12
A physician-centered AI system is being built to help diagnose and treat bloodstream infections more accurately and safely, with the goal of reducing sepsis deaths.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Central Florida NIH-funded |
| Lab location | 1 site (Orlando, United States) |
| Project start | September 9, 2026 |
| Project end | August 31, 2030 |
| Funding year | 2026 |
| Award (this year) | $299,751 |
| NIH project number | 1R01AI206896-01 |
| Project ID | NIH-11579169 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates are adults with suspected or confirmed bacteremia, or patients at risk of bloodstream infections who would benefit from improved diagnostic and treatment decision support.
✕Less likely to help
Patients whose infections are not bloodstream-related or whose clinical needs fall outside the AI system’s scope may not benefit.
What this research studies
This project aims to create an end-to-end AI assistant that works with clinicians to streamline the steps from risk assessment to selecting antibiotics for bacteremia. It will use multiple specialized AI agents that handle different parts of care, all coordinated by a central critic that checks consistency and calibrates recommendations. The system will ground its reasoning in medical knowledge and clinician input to ensure trustworthy guidance. It focuses on improving accuracy, equity, and safety while supporting antimicrobial stewardship. Researchers will validate the approach across sites to promote adoption in real-world hospital settings.
Why it matters
Potential benefit: If successful, patients with bloodstream infections could receive faster, more accurate treatment and potentially lower risk of sepsis-related death.
How similar studies have gone: Previous efforts show that AI can improve parts of the infection-management workflow, but end-to-end, physician-centered, multi-agent systems with site validation are novel/less proven.
Where this research is happening
-
University of Central Florida
Orlando, United States Active
Researchers
- Principal investigator: Lou, Qian — University of Central Florida
- Study coordinator: Lou, Qian
Related research
Other NIH-funded projects on the same topics.
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Rapid pathogen ID and antibiotic testing for bacteremia using immune capture, microfluidics, and AI
A fast, AI-assisted diagnostic system will identify bacteria in blood and determine which antibiotics are likely to work, helping doctors treat bacteremia sooner.
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This grant studies how innate immune cells called macrophages protect against Klebsiella pneumoniae bloodstream infections to help reduce sepsis mortality.
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Epigenomic clues and immune context in stubborn MRSA bloodstream infections
Researchers are studying why some MRSA bloodstream infections persist despite antibiotics and how the immune system and bacterial DNA packaging (epigenetics) influence this, with the goal of better treatments.
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Liposome-delivered rebamipide as an add-on treatment for Staphylococcus aureus bacteremia
A biotech company is testing a liposome-formulated rebamipide to help the body fight Staphylococcus aureus bloodstream infections alongside standard antibiotics.
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.