Improving diagnosis of shortness of breath using AI and clinician collaboration
Official title: Human-AI Collaborations to Improve Accuracy and Mitigate Bias in Acute Dyspnea Diagnosis
Funded at University of Michigan at Ann Arbor · NIH-10909198 · Data updated 2026-11-12
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 start | September 20, 2021 |
| Project end | August 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $665,592 |
| NIH project number | 5R01HL158626-04 |
| Project ID | NIH-10909198 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are patients experiencing acute dyspnea, particularly those with conditions like heart failure, pneumonia, or chronic obstructive pulmonary disease.
✕Less likely to help
Patients with stable chronic respiratory conditions who do not experience acute episodes of dyspnea may not benefit from this research.
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.
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 gone: 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
-
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
Related research
Other NIH-funded projects on the same topics.
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Patient-centered risk profiling to tailor breathlessness care
A study from UCLA aims to use AI to identify why a smoker experiences shortness of breath and tailor care to each person.
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Understanding how the brain shapes breathing to help people with persistent breathlessness
Researchers are studying how higher brain regions influence breathing and the feeling of breathlessness in people with conditions like COPD and asthma, with the goal of safer, non-ventilation-impairing treatments.
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Predicting and continuously monitoring breathlessness with noninvasive signals
A study to create a machine-learning tool that uses easy-to-measure body signals to predict when patients feel breathless, even if they can’t communicate.
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Personalized oxygen and breathing support for cancer-related breathlessness
This trial compares a respiratory-therapist-led program that tailors oxygen and other breathing supports to help hospitalized patients with advanced cancer who are bothered by breathlessness.
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How the brain creates ongoing breathlessness
Researchers are recording brain signals from people who already have implanted epilepsy electrodes to understand how higher brain regions produce ongoing breathlessness in conditions like COPD, asthma, heart or neuromuscular disease.
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Brief behavioral support to help breathlessness in advanced lung cancer
A multi-site study tests a short behavioral program delivered by nurses to help adults with advanced lung cancer feel less breathless and more able to do daily activities.
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.