Our Research

Harnessing the power of “real-world” data to improve diagnosis, treatment, and outcomes in ophthalmology:

Diabetic retinopathy:
- Prediction models for progression of diabetic retinopathy
- Role of social determinants of health in disease progression
- Clinical decision support tool for patients and clinicians
Glaucoma:
- Emulating glaucoma randomized clinical trials using observational data
- Improving neovascular glaucoma outcomes
- Clinical outcomes of laser trabeculoplasty
- Infection rates following tonometry measurement
- Risk factors of acute angle closure attack
Cataract outcomes:
- Impact of telehealth on cataract post-operative management
- Risk factors for zonulopathy
Pterygium outcomes:
- Office-based pterygium surgery outcomes

Automated classification approaches using natural language processing and large language models for diabetic retinopathy and glaucoma
Comparing diagnosis codes to automated classification approaches for cohort selection
Improving detection of disease duration and social determinants of health from clinical notes

Planning phase to lay the necessary foundation for future RRCTs in ophthalmology