Wang Sophia Y

Predicting Glaucoma Progression Requiring Surgery Using Clinical Free-Text Notes and Transfer Learning With Transformers.

Using transfer learning with massively pre-trained BERT-based models is a natural language processing approach that can access the wealth of clinical information stored within ophthalmology clinical notes to predict the progression of glaucoma.

Phase 1b Randomized Controlled Study of Short Course Topical Recombinant Human Nerve Growth Factor (rhNGF) for Neuroenhancement in Glaucoma: Safety, Tolerability, and Efficacy Measure Outcomes.

Use of rhNGF is safe and tolerable in a topical 180-μg/mL formulation.

Intraocular Pressure Changes after Cataract Surgery in Patients with and without Glaucoma: An Informatics-Based Approach.

Our results suggest that patients with primary open-angle glaucoma or with narrow angles or chronic angle closure were more likely to achieve sustained IOP reduction after cataract surgery.

The Association among Blood Pressure, Blood Pressure Medications, and Glaucoma in a Nationwide Electronic Health Records Database.

We found that low BP is associated with increased risk of developing OAG in a national longitudinal EHR database.

Ocular Antihypertensive Medication Use After iStent Implantation Concurrent With Cataract Surgery vs Cataract Surgery Alone in a Large US Health Care Claims Database.

Implantation of the iStent trabecular micro-bypass stent concurrent with cataract surgery was associated with moderately reduced use of topical ocular antihypertensive medication.

Blood Pressure Measures and Incident Primary Open-Angle Glaucoma.

Higher SBP and PP were associated with an increased risk of incident POAG. Further studies are required to characterize these relationships better.

Predicting Glaucoma Surgical Outcomes Using Neural Networks and Machine Learning on Electronic Health Records.

ML and DL algorithms can predict glaucoma surgery outcomes using structured data inputs from EHRs.

Multimodal Artificial Intelligence Models Predicting Glaucoma Progression Using Electronic Health Records and Retinal Nerve Fiber Layer Scans.

Fusion models which integrate both RNFL with EHR data outperform models only utilizing one datatype or the other to predict glaucoma progression. The deep learning TabNet architecture demonstrated superior performance to traditional XGBoost models.

Real-World Outcomes of Glaucoma Filtration Surgery Using Electronic Health Records: An Informatics Study.

Baerveldt and Ahmed tube shunt implantation was associated with increased failure compared with trabeculectomy.

Gap Analysis of Glaucoma Examination Concept Representations within Standard Systemized Nomenclature of Medicine - Clinical Terms.

There are existing gaps in the standardized representation of findings related to tonometry and gonioscopy within SNOMED-CT.

Gap Analysis of Standard Automated Perimetry Concept Representation in Medical Terminologies.

There is a lack of representation of some SAP data elements in standardized medical terminologies, hampering interoperability and data sharing.

Corrigendum to Phase 1b Randomized Controlled Study of Short Course Topical Recombinant Human Nerve Growth Factor (rhNGF) for Neuroenhancement in Glaucoma: Safety, Tolerability, and Efficacy Measure Outcomes. Am J Ophthalmol 2022;234:223-234.

Beyond PhacoTrainer: Deep Learning for Enhanced Trabecular Meshwork Detection in MIGS Videos.

Building on prior work developing computer vision models for cataract surgical video, we developed models that recognize MIGS procedures and precisely localize the TM with superior performance.

Impact of Type 2 diabetes mellitus and insulin use on progression to glaucoma surgery in primary open angle glaucoma.

Higher baseline HbA1c, particularly in patients taking insulin may be associated with higher rates of glaucoma surgery in POAG.