AI • Healthcare
Fundusnap
AI diabetic retinopathy screening
A healthcare AI project for detecting diabetic retinopathy from retinal/fundus images to support more accessible early screening.
Project focus
Computer vision for retinal image analysis
Case study
Fundusnap is a healthcare AI project for diabetic retinopathy screening from retinal images. The project page emphasizes computer vision, machine learning, and accessible early screening support.
Problem
Early screening for diabetic retinopathy depends on retinal image review, but access and triage can be uneven. Fundusnap explores how computer vision can support a more accessible first-pass screening workflow.
Approach
The project uses Python, computer vision, and machine learning for retinal image analysis. The portfolio page frames the work around screening support rather than replacing clinical judgment.
Outcome
The project won the Microsoft ElevAIte Hackathon, giving the healthcare AI case study a concrete recognition signal.
Recognition
Winner - Microsoft ElevAIte Hackathon