Predicting Anti-VEGF Therapy Response in Wet-AMD Patients
Program:
Biomedical Engineering
Project Description:
In this project, we aim to predict wet age-related macular degeneration patients’ responses to anti-VEGF therapies using machine learning. Wet age-related macular degeneration (AMD) is the leading cause of vision loss in people over 50 and is known for its rapid progression, making ophthalmologists’ early and decisive treatment selection critical in maintaining quality of life for the patient. Anti-VEGF injections are the current gold-standard treatment, but they do not work for about 15-20% of patients. We are using data collected through an IRB with the Johns Hopkins Wilmer Eye Insitute to train a machine learning algorithm to predict whether an eye will respond well to anti-VEGF therapy to allow ophthalmologists to make personalized treatment plans for wet AMD patients.
Team Members
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Project Mentors, Sponsors, and Partners
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Alvin Liu
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Craig Jones
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Neslihan Koseoglu
Course Faculty
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