Kazemian Pooyan

Personalized Prediction of Glaucoma Progression Under Different Target Intraocular Pressure Levels Using Filtered Forecasting Methods.

To our knowledge, this is the first clinical decision-making tool that generates personalized forecasts of the trajectory of OAG progression at different target IOP levels.

Comparing Perimetric Loss at Different Target Intraocular Pressures for Patients with High-Tension and Normal-Tension Glaucoma.

Machine learning algorithms using Kalman filtering techniques demonstrate promise at forecasting future MD values at different target IOPs for patients with NTG and HTG.