NeuroSight: Bridging Oculomic and Acoustic Features for Multi-Disease Prediction via Deep Learning
CWSF · 2026 Disease & Illness Bronze Medal
Overview
Current diagnostic methods for neurodegenerative diseases often depend on expensive imaging or on symptoms that only appear in later stages. My project, NeuroSight, explores a more accessible way to flag early warning signs. I developed a low-cost, 3D‑printed fundus camera integrated with a high‑fidelity microphone to capture retinal images and voice recordings at the same time. Using a multi‑modal deep learning model, NeuroSight analyzes subtle microvascular thinning in the eye and vocal instability to identify potential pathological markers with high accuracy. These results suggest that a non‑invasive, affordable hardware–software system could deliver lab‑grade diagnostic insight and help bring earlier screening to communities that currently lack access to advanced clinical tools.
Awards (3)
- Special Award
- Bronze Medal
- Selected for CWSF 2026
Competition history
- CWSF 2026
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