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Research

Led Dr Sophia Wang, our research group’s goal is to perform cutting-edge research that leads at the interface of informatics and ophthalmology, to be able to rapidly and accurately deliver health insights from large volumes of data to improve ophthalmology patient care. Our research group uses and integrates a wide variety of data sources in our research, spanning both structured and unstructured forms, including national survey datasets, health insurance claims data, patient generated online text, and electronic health records. We investigate outcomes of treatments for glaucoma and cataract, as well as other areas of ophthalmology, while developing and applying novel methods for automated extraction of ophthalmic data from free text.

Current Projects

We are currently working on projects in several areas, including the following: 

  • Developing, validating, and applying natural language processing methods for ophthalmology clinical text 
  • Developing artificial intelligence deep learning algorithms on electronic health records data to predict glaucoma progression 
  • Developing artificial intelligence deep learning algorithms on electronic health records data to predict glaucoma surgical outcomes 
  • Developing artificial intelligence deep learning algorithms on electronic health records data to predict visual prognosis of patients with low vision 
  • Developing artificial intelligence computer vision algorithms for cataract surgical videos, to detect the activity being performed, and to detect the identity and location of eye anatomical landmarks and instruments being used 
  • Investigating associations between glaucoma and a variety of risk factors using data from insurance claims and national registries 
  • Investigating glaucoma surgical outcomes using data from insurance claims, national registries, and electronic health records