Improving glaucoma detection and prediction using artificial intelligence.
SCH: Robust and Equitable Clinical Decision Support in Glaucoma Detection and Progression Prediction
This study is working on a smart tool that uses artificial intelligence to help doctors spot and predict glaucoma earlier by looking at different types of eye tests, so patients can get better care and keep their vision longer.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pennsylvania NIH-funded |
| Lab location | 1 site (Philadelphia, United States) |
| Project ID | NIH-11063429 on NIH RePORTER |
What this research studies
This research focuses on enhancing the detection and prediction of glaucoma, a progressive eye disease that can lead to vision loss. By developing an artificial intelligence-based clinical decision support tool, the project aims to integrate various types of patient data, such as retinal imaging and visual field measurements, to improve diagnostic accuracy. The tool will also be designed to help clinicians make informed decisions by providing clear insights into the AI's predictions and uncertainties. Ultimately, this approach seeks to facilitate earlier interventions and better management of glaucoma.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals at risk for glaucoma or those experiencing early symptoms of vision impairment.
Not a fit: Patients with advanced glaucoma who have already experienced significant vision loss may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to earlier and more accurate diagnoses of glaucoma, potentially preventing vision loss for many patients.
How similar studies have performed: Previous research has shown promise in using AI for disease detection, suggesting that this approach could lead to significant advancements in glaucoma management.
Where this research is happening
Philadelphia, United States
- University of Pennsylvania — Philadelphia, United States (Active)
Researchers
- Principal investigator: Lee, Insup — University of Pennsylvania
- Study coordinator: Lee, Insup
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.