Using deep learning to detect and predict glaucoma progression from eye scans
Deep Learning Approaches to Detect Glaucoma and Predict Progression from Spectral Domain Optical Coherence Tomography
This study is looking at how we can better spot and track primary open angle glaucoma using advanced computer technology, so that patients can get the help they need sooner and manage their condition more effectively.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California, San Diego NIH-funded |
| Lab location | 1 site (La Jolla, United States) |
| Project ID | NIH-11081725 on NIH RePORTER |
What this research studies
This research focuses on improving the detection and monitoring of primary open angle glaucoma (POAG), a leading cause of blindness. By utilizing advanced deep learning techniques, the study aims to analyze data from optical coherence tomography (OCT) and visual field tests, along with patient demographics and medical history. The goal is to create predictive models that can accurately forecast the progression of glaucoma, allowing for earlier intervention and better management of the disease.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals diagnosed with primary open angle glaucoma or those at risk of developing the condition.
Not a fit: Patients with other types of glaucoma or those who do not have access to the necessary imaging technologies may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier detection and more effective treatment strategies for patients with glaucoma, potentially preserving vision.
How similar studies have performed: Other research has shown promising results using deep learning approaches for similar diagnostic challenges, indicating potential for success in this area.
Where this research is happening
La Jolla, United States
- University of California, San Diego — La Jolla, United States (Active)
Researchers
- Principal investigator: Christopher, Mark — University of California, San Diego
- Study coordinator: Christopher, Mark
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.