Developing advanced AI tools for real-time clinical decision-making
TRD3: Data Analytics and Intelligent Systems (AI-ML-DL-Visualization)
This study is working on new technology that uses artificial intelligence to help doctors see and understand medical images better during surgeries and in intensive care, which could lead to quicker and more accurate treatments for patients.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California at Davis NIH-funded |
| Lab location | 1 site (Davis, United States) |
| Project ID | NIH-11105989 on NIH RePORTER |
What this research studies
This research focuses on creating innovative artificial intelligence (AI) and machine learning (ML) tools to enhance real-time imaging and data integration during critical clinical procedures, such as surgery and intensive care. The project aims to develop advanced visualization systems that can combine various types of medical data to support healthcare professionals in making informed decisions quickly. By optimizing both the imaging hardware and the AI algorithms, the research seeks to improve the accuracy and efficiency of clinical workflows. Patients may benefit from improved outcomes due to more precise and timely interventions facilitated by these technologies.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients undergoing surgical procedures or receiving intensive care who may benefit from enhanced imaging and data integration.
Not a fit: Patients not undergoing critical procedures or those with stable conditions that do not require real-time decision-making may not receive benefits from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate and timely medical interventions, ultimately improving patient outcomes in critical care settings.
How similar studies have performed: Previous research has shown promise in using AI and ML for improving clinical decision-making, indicating that this approach has the potential for significant advancements.
Where this research is happening
Davis, United States
- University of California at Davis — Davis, United States (Active)
Researchers
- Principal investigator: Qi, Jinyi — University of California at Davis
- Study coordinator: Qi, Jinyi
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.