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Nazlee Zebardast, M.D.

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Ophthalmic Data Science [login at prompt]
Available: 03/01/24, Expires: 03/01/26

Multiple projects are available for highly motivated student in the field of ophthalmic epidemiology and data science. Background in statistics and knowledge of statistical and computer programming is helpful. 1. Genomics and disease risk prediction. Using two large biobanks and results from a large ophthalmic clinical trial, these projects aim to understand the influence of polygenic risk on glaucoma disease risk, phenotype, and progression. 2. Machine learning. Using large existing datasets these projects aim to use machine learning for better disease prognostication. Unsupervised and semi supervised deep learning models will be used on large repositories of ophthalmic imaging to understand subtypes of disease and characterize progression. The goal is to define structural and longitudinal endophenotypes that are closely aligned with disease type, severity, and progression. 3. Outcomes and health equity research. Multiple datasets are available for use including a large ophthalmic registry, large EHR database and Medicare datasets. We have previously used these datasets to understand the effectiveness of new surgical procedures in the US and racial healthcare inequities among glaucoma patients. Student role: The primary goal of these projects is for the students to learn how to handle large amounts of healthcare data and perform appropriate statistical analysis. The student will formulate the research question and use existing data to answer these questions. The goal is that the student will take ownership of a project and bring it to fruition by planning and completing at least one manuscript. The student can decide on the question most interesting to them or work with the mentor to join an existing project. Student and mentor will meet at least weekly (and more often as needed) to ensure adequate progress.

The research activities and funding listed below are automatically derived from NIH ExPORTER and other sources, which might result in incorrect or missing items. Faculty can login to make corrections and additions.
  1. R21EY032953 (ZEBARDAST, NAZLEE) Sep 30, 2021 - Jul 31, 2023
    Sociodemographic predictors of healthcare utilization and adverse outcomes in Medicare beneficiaries with glaucoma
    Role: Principal Investigator
  2. K23EY032634 (ZEBARDAST, NAZLEE) Jul 1, 2021 - May 31, 2025
    Glaucoma Risk Prediction Using Machine Learning Integration of Image-Based Phenotypes and Genetic Associations
    Role: Principal Investigator
  3. R01EY032559 (PASQUALE, LOUIS ROBERT ;WIGGS, JANEY L) Jul 1, 2021 - May 31, 2025
    Understanding the clinical impact of cumulative genetic risk to glaucoma
    Role: Co-Investigator
  4. RPB CDA (Nazlee Zebardast) Jun 1, 2021 - May 31, 2025
    Research to Prevent Blindness
    Clinical features and genetic risk factors associated with machine-learning-derived image-based glaucoma subtypes

Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
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Funded by the NIH National Center for Advancing Translational Sciences through its Clinical and Translational Science Awards Program, grant number UL1TR002541.