Domain-specific Vision Foundation Model - OpthaDetect
Aside from my academic endeavours in teaching and researching ICT4D, I am also committed to developing projects that can solve problems beyond the classroom. In the second year of my PhD, I was selected as a year-long fellow of Cambridge King's (College) Entrepreneurship lab, where I pitched a project to solve social media communication problems for universities and academic enterprises in Africa. The success of my pitch and fellowship has encouraged me to partner and collaborate to develop more projects that can solve societal needs.
In particular, I am working with a machine learning engineer, Rodiyah Oluwa, to develop solutions to track Diabetic Retinopathy (DR) faster in growth markets. Globally, getting results from eye scans takes 1 to 7 days. Our project, OpthaDetect, specifically seeks to reduce the wait time for DR to seconds, providing a confidence level statement for all results.
DR is a progressive complication of diabetes and remains one of the leading causes of preventable vision loss worldwide. Early and accurate detection is essential to improving patient outcomes, especially in low-resource settings where access to specialist ophthalmic care is limited. OpthaDetect, therefore, applies deep learning for automated DR detection using high-resolution retinal fundus images.
Our start-up received the prestigious 2026 (Cambridge) King's Entrepreneurship Prize. Our platform can be accessed here.