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
-
[foreach 357]
[if 397 not_equal=””][/if 397][395]
[/foreach 357]
Project Mentors, Sponsors, and Partners
Alvin Liu
Craig Jones
Neslihan Koseoglu
Course Faculty
-
[foreach 429]
[if 433 not_equal=””][/if 433][431]
[/foreach 429]
Project Links
Additional Project Information
Project Photo
Project Photo Caption:
A cartoon of an eye with the colors of an Optical Coherence Tomography image depth map turns into a silver-colored technological circuit.