Creating fair AI models for glaucoma screening
Developing Equitable Deep Learning Models for Automated Glaucoma Screening
['FUNDING_R01'] · SCHEPENS EYE RESEARCH INSTITUTE · NIH-10872671
This study is working on using smart computer technology to help find glaucoma early, especially for people from different backgrounds who might not have easy access to eye care, so that everyone can get the right diagnosis without needing expensive specialist visits.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | SCHEPENS EYE RESEARCH INSTITUTE (nih funded) |
| Locations | 1 site (BOSTON, UNITED STATES) |
| Trial ID | NIH-10872671 on ClinicalTrials.gov |
What this research studies
This research focuses on developing advanced deep learning models to detect glaucoma, a leading cause of blindness, particularly among underserved racial and ethnic groups. By utilizing retinal imaging, the project aims to provide affordable glaucoma screening that can be implemented in primary care settings, reducing the need for costly visits to specialized eye clinics. The study will assess the equity of these models by examining their performance across various demographic factors, ensuring that all groups receive accurate diagnoses. The approach includes using optical coherence tomography scans and fundus photos to predict glaucoma based on established clinical guidelines.
Who could benefit from this research
Good fit: Ideal candidates for this research include individuals from racial and ethnic minority groups who may be at higher risk for glaucoma and have limited access to eye care.
Not a fit: Patients who do not have glaucoma or those who have already received adequate screening and treatment may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more equitable and accessible glaucoma screening, ultimately reducing blindness rates in vulnerable populations.
How similar studies have performed: Previous research has shown promise in using AI for medical diagnostics, but this specific approach to equitable glaucoma detection is novel and has not been extensively tested.
Where this research is happening
BOSTON, UNITED STATES
- SCHEPENS EYE RESEARCH INSTITUTE — BOSTON, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: WANG, MENGYU — SCHEPENS EYE RESEARCH INSTITUTE
- Study coordinator: WANG, MENGYU
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.