Improving diagnosis of shortness of breath using AI and clinician collaboration
Human-AI Collaborations to Improve Accuracy and Mitigate Bias in Acute Dyspnea Diagnosis
This study is looking at how we can use artificial intelligence to help doctors better diagnose sudden breathing problems, making sure patients get the right care when they visit the emergency room.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Michigan at Ann Arbor NIH-funded |
| Lab location | 1 site (Ann Arbor, United States) |
| Project ID | NIH-10909198 on NIH RePORTER |
What this research studies
This research focuses on enhancing the accuracy of diagnosing acute dyspnea, a common cause of emergency visits, by leveraging artificial intelligence (AI) tools. It aims to develop and test strategies that improve the collaboration between clinicians and AI systems to ensure better diagnostic outcomes. The project will evaluate computational methods to make AI tools more reliable and will assess how these tools can effectively support healthcare providers in real clinical settings. By addressing the challenges of diagnostic errors, particularly in complex cases, this research seeks to improve patient care.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients experiencing acute dyspnea, particularly those with conditions like heart failure, pneumonia, or chronic obstructive pulmonary disease.
Not a fit: Patients with stable chronic respiratory conditions who do not experience acute episodes of dyspnea may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more accurate diagnoses of acute dyspnea, resulting in better treatment outcomes for patients.
How similar studies have performed: Previous research has shown promise in using AI to assist in clinical diagnostics, indicating that this approach could yield significant improvements in patient care.
Where this research is happening
Ann Arbor, United States
- University of Michigan at Ann Arbor — Ann Arbor, United States (Active)
Researchers
- Principal investigator: Sjoding, Michael William — University of Michigan at Ann Arbor
- Study coordinator: Sjoding, Michael William
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.