Wang Mengyu

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.

Sex-Specific Differences in Circumpapillary Retinal Nerve Fiber Layer Thickness.

Substantial sex effects on cRNFL thickness were found at 56.8% of all 768 circumpapillary locations, with specific patterns for different sectors.

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.

Race and Ethnicity Differences in Disease Severity and Visual Field Progression Among Glaucoma Patients.

Black, Asian and Hispanic patients had greater baseline severity vs.

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…

An Artificial Intelligence Approach to Assess Spatial Patterns of Retinal Nerve Fiber Layer Thickness Maps in Glaucoma.

Using RPs improved the VF prediction compared with using sectoral RNFLTs.

Microvasculature of the Optic Nerve Head and Peripapillary Region in Patients With Primary Open-Angle Glaucoma.

The image processing methodology based on the anatomic boundary of ONH demonstrated compromised microvasculature in the deep ONH and peripapillary region in eyes with mild to moderate POAG, regardless of the history of DH.

Cohort Study of Race/Ethnicity and Incident Primary Open-Angle Glaucoma Characterized by Autonomously Determined Visual Field Loss Patterns.

Blacks, compared to non-Hispanic whites, had higher risks of POAG with early central and advanced VF loss.

Relationship Between Central Retinal Vessel Trunk Location and Visual Field Loss in Glaucoma.

CRVTL nasalization is significantly and exclusively correlated to central VF loss for all glaucoma severities independent of cpRNFLT, and thus might be a structural biomarker of central VF loss.

Associations between Optic Nerve Head-Related Anatomical Parameters and Refractive Error over the Full Range of Glaucoma Severity.

Our results suggest that SE should be considered when interpreting the OD and its circumpapillary region for diagnostic purposes.

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.

Estimating the Severity of Visual Field Damage From Retinal Nerve Fiber Layer Thickness Measurements With Artificial Intelligence.

The proposed ANN model estimated MD from RNFL measurements better than multivariable linear regression model, random forest, support vector regressor, and 1-D CNN models.

Paired Optic Nerve Microvasculature and Nailfold Capillary Measurements in Primary Open-Angle Glaucoma.

Patients with POAG demonstrated morphologic and hemodynamic alterations in both ophthalmic and nailfold microvascular beds compared to controls.

Norms of Interocular Circumpapillary Retinal Nerve Fiber Layer Thickness Differences at 768 Retinal Locations.

We provide pointwise normative distributions of interocular cpRNFLT differences at an unprecedentedly high spatial resolution of 768 A-scans and reveal considerable location specific asymmetries as well as their associations with age and scanning radius differences…

The Interrelationship between Refractive Error, Blood Vessel Anatomy, and Glaucomatous Visual Field Loss.

BV locations outside the ONH are sufficiently stable over glaucoma severity to represent individual eye anatomy, and the IAA at 1.73 mm eccentricity is the optimal parameter to be considered for novel OCT RNFLT norms.

Artifact Correction in Retinal Nerve Fiber Layer Thickness Maps Using Deep Learning and Its Clinical Utility in Glaucoma.

Artifact correction for RNFLTs improves VF and progression prediction in glaucoma.

An Objective and Easy-to-Use Glaucoma Functional Severity Staging System Based on Artificial Intelligence.

We discovered that 4 severity levels based on MD thresholds of -2.2, -8.0, and -17.3 dB, provides the optimal number of severity stages based on unsupervised and supervised machine learning.

Normative Percentiles of Retinal Nerve Fiber Layer Thickness and Glaucomatous Visual Field Loss.

Our results challenge the assumption that normative percentiles from OCT machines improve prediction of glaucomatous visual field loss.

Comparison of Structural and Functional Features in Primary Angle Closure and Open Angle Glaucomas.

Patients with PACG had less structural damage than patients with POAG despite similar degrees of functional loss.

Quantification of the Peripapillary Microvasculature in Eyes with Glaucomatous Paracentral Visual Field Loss.

Regional peripapillary microvasculature showed decreased VD and flow in POAG with paracentral loss, supporting its importance in this glaucoma subtype.

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.

Accuracy of ICD-10 Glaucoma Codes in a Large Academic Practice.

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.

Artifacts in OCT Retinal Nerve Fiber Layer Imaging in Patients with Boston Keratoprosthesis Type 1.

The rate of OCT RNFL images with either poor signal strength or artifacts in the KPro and control population was comparable.

Contributions of Brain Microstructures and Metabolism to Visual Field Loss Patterns in Glaucoma Using Archetypal and Information Gain Analyses.

Our findings highlight the importance of non-invasive neuroimaging biomarkers and analytical modeling for unveiling glaucomatous neurodegeneration and how they reflect complementary VF loss patterns.

Assessing the Accuracy of Artificial Intelligence-Generated Clinical Summaries From Ambulatory Glaucoma Subspecialty Clinical Encounters.

Although LLaMA 2 is not yet reliable as a standalone clinical tool, it shows promise to improve clinical communication.

Geographic Distribution of Access to Glaucoma Surgery: An IRIS® Registry (Intelligent Research in Sight) Analysis.

Patients are more likely to receive most types of glaucoma surgeries in urban practice locations.

Association Between Cup-to-Disc Ratio and Structural and Functional Damage Parameters in Glaucoma: Insights From Multiparametric Modeling.

CDR is subject to ceiling effects for glaucoma-related outcomes and poor at discriminating early glaucomatous damage. CDR values should be interpreted with care, particularly in screening settings.

Combined Model of OCT Angiography and Structural OCT Parameters to Predict Paracentral Visual Field Loss in Primary Open-Angle Glaucoma.

A combined model of OCTA and structural OCT parameters can predict the severity of paracentral VF loss of the affected hemifield, supporting clinical utility of OCTA in patients with POAG with paracentral VF loss.

ChatGPT-Assisted Glaucoma Diagnosis: A Health-Equitable Multi-Ancestry Analysis Using Visual Field and Optical Coherence Tomography Data.

ChatGPT o1 Pro diagnosed glaucoma similarly to specialists using only VF and OCT data. The model performance was similar across ancestral groups and genetic predispositions to glaucoma.

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.

Generative Artificial Intelligence for Retinal Image Translation to Improve Glaucoma Screening With Deep Learning.

GANs effectively translate SLO images into synthetic CF photographs, addressing domain shifts and increasing dataset sizes to enhance glaucoma detection.

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.

Genetic Risk for Open-Angle Glaucoma Subtypes Is Associated with Specific Visual Field Defect Classes.

Higher POAG PRSs and NTG PRSs were associated with paracentral VF loss, whereas higher HTG GRS was linked to total VF loss, but not paracentral defects.

Impact of Demographics on Regional Visual Field Loss and Deterioration in Glaucoma.

Blacks and non-English speakers have more severe VF loss, with superior hemifield being more affected and faster VF worsening.

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