Using deep learning to identify features of shoulder fractures
The Application of Deep Learning Methods for Proximal Humerus Fracture Feature Identification
This study is looking to make it easier for doctors to understand and treat shoulder fractures in older adults by using advanced computer technology to analyze X-rays, so patients can get better and more personalized care.
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-10912651 on NIH RePORTER |
What this research studies
This research focuses on improving the classification and treatment of proximal humerus fractures (PHFs), which are common in elderly patients. By applying deep learning methods to analyze imaging data, the project aims to automate the identification of fracture characteristics, which can help determine the most effective treatment options. The study seeks to address the current inconsistencies in fracture classification and treatment decisions, ultimately enhancing patient care. Patients may benefit from more accurate diagnoses and tailored treatment plans based on their specific fracture characteristics.
Who could benefit from this research
Good fit: Ideal candidates for this research are elderly adults who have sustained proximal humerus fractures.
Not a fit: Patients with fractures other than proximal humerus fractures or those who are not elderly may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to improved treatment outcomes and reduced long-term disability for patients with shoulder fractures.
How similar studies have performed: Other research has shown promise in using deep learning for medical imaging analysis, indicating potential success for this approach.
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.