Sarah R. Wellik

An Artificial Intelligence Approach to Detect Visual Field Progression in Glaucoma Based on Spatial Pattern Analysis.

The archetype method can inform clinicians of VF progression patterns.

Artificial Intelligence Classification of Central Visual Field Patterns in Glaucoma.

We quantified central VF patterns in glaucoma, which were used to improve the prediction of central VF worsening compared with using only global indices.

Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence.

In this study, central VF loss in end-stage glaucoma was found to exhibit characteristic patterns that might be associated with different subtypes.

Reversal of Glaucoma Hemifield Test Results and Visual Field Features in Glaucoma.

Using VF features may predict the GHT results reversal to WNL after 2 consecutive ONL results.

Agreement and Predictors of Discordance of 6 Visual Field Progression Algorithms.

This extremely large comparative series demonstrated that existing algorithms have limited agreement and that agreement varies with clinical parameters, including institution.

Monitoring Glaucomatous Functional Loss Using an Artificial Intelligence-Enabled Dashboard.

The AI-enabled glaucoma dashboard, developed using a large VF dataset containing a broad spectrum of visual deficit types, has the potential to provide clinicians with a user-friendly tool for determination of the severity of glaucomatous…

A Comparative Study of Central Corneal Epithelial, Stromal, and Total Thickness in Males With and Without Primary Open-Angle Glaucoma.

Individuals with glaucoma have lower CST and CCT measurements compared with individuals without glaucoma. An increased number of glaucoma medications were associated with lower thickness measurements.

Predicting Global Test-Retest Variability of Visual Fields in Glaucoma.

Inclusion of archetype VF loss patterns and TD values based on first VF improved the prediction of the global test-retest variability than using traditional global VF indices alone.

Baseline Age and Mean Deviation Affect the Rate of Glaucomatous Vision Loss.

Older age and worse MD at baseline are associated with more rapid VF progression in this large dataset.

Development and Comparison of Machine Learning Algorithms to Determine Visual Field Progression.

MLCs showed a moderate to high level of accuracy, sensitivity, and specificity and were more balanced than conventional algorithms.

Variability and Power to Detect Progression of Different Visual Field Patterns.

Time to detect central VF progression was reduced with 10-2 MD compared with 24-2 and C24-2 MD in glaucoma eyes in this large dataset, in part because 10-2 tests had lower variability.

Inter-Eye Association of Visual Field Defects in Glaucoma and Its Clinical Utility.

VF patterns of the worse eye are predictive of VF defects in the better eye.

Transformer-Based Deep Learning Prediction of 10-Degree Humphrey Visual Field Tests From 24-Degree Data.

The predicted 10-2 VF has the potential to improve glaucoma diagnosis.

Dual-Level Pattern Tree for Visual Field Improves Glaucoma Progression and Polygenic Risk Prediction.

Trunk-branch VF classifiers were superior to trunk-only characterizations for predicting functional progression and glaucoma PRS.

The Impact of Myopia on Regional Visual Field Loss and Progression in Glaucoma.

Lower SE values are associated with worse paracentral VF loss. Worse myopia is associated with functional progression, even when excluding patients with high myopia.

Reply.

In Reply.

Refractive outcomes of combined cataract and glaucoma surgery.

Favorable refractive outcomes were achieved in the majority of patients despite the potential alteration of preoperative measurements and introduction of error into lens selection when using a combined approach.

Brimonidine allergy presenting as vernal-like keratoconjunctivitis.

Direct medication allergy and ocular surface disease are two distinct entities that often co-exist. Distinguishing between the two entities, sometimes by trial and error, is critical in the management of these patients.