AI that reads shoulder X-rays to identify upper-arm (proximal humerus) fracture features
The Application of Deep Learning Methods for Proximal Humerus Fracture Feature Identification
This project uses artificial intelligence to read shoulder X-rays and label features of upper-arm fractures in adults so doctors can make more consistent treatment decisions.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Clemson University NIH-funded |
| Lab location | 1 site (Clemson, United States) |
| Project ID | NIH-11176137 on NIH RePORTER |
What this research studies
If I have a shoulder fracture, the team will use computer algorithms trained on X-rays to find and label fracture parts and patterns that doctors currently describe with the Neer system. The work aims to make those labels more consistent and complete by teaching deep learning models to detect fracture features automatically. The researchers plan to use collections of patient X-rays and imaging data to train and test the models and compare the AI labels to human experts. The hope is that clearer, standardized imaging information will help guide care choices for older adults with these fractures.
Who could benefit from this research
Good fit: Adults (including older adults) with a recent proximal humerus (upper-arm/shoulder) fracture who have shoulder X-rays could be the intended group to contribute images or participate.
Not a fit: People without shoulder X-rays, those with other types of arm fractures, or children are unlikely to benefit directly from this work.
Why it matters
Potential benefit: If successful, this could give doctors more reliable, standardized fracture information to help choose the right treatment faster.
How similar studies have performed: Deep learning has shown promise for detecting fractures on X-rays, but automated, reliable classification of proximal humerus fracture features is less established and still being tested.
Where this research is happening
Clemson, United States
- Clemson University — Clemson, United States (Active)
Researchers
- Principal investigator: Floyd, Sarah Bauer — Clemson University
- Study coordinator: Floyd, Sarah Bauer
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.