AI-Powered Diabetic Retinopathy Diagnosis for Early Detection

Executive Summary

Diabetic retinopathy (DR) is a leading cause of blindness among adults, but early detection and timely treatment can prevent up to 90% of vision loss cases. Recognizing the critical need for accessible and efficient screening, we partnered with a regional healthcare provider serving a large diabetic population.

About the Client

The client is a regional healthcare provider dedicated to offering comprehensive care to a large and growing diabetic population. With a focus on community health, the organization operates multiple facilities, including clinics in rural and underserved areas, where access to specialized care is often limited.

As diabetes prevalence surged, the healthcare provider faced mounting challenges in managing diabetic retinopathy screenings due to resource constraints, a shortage of specialists, and operational inefficiencies. Committed to improving patient outcomes, the client sought an innovative AI-driven solution to enhance early detection, streamline screening processes, and expand accessibility to critical diagnostic services, especially for at-risk populations in remote regions.

Solution Overview

We developed an AI-driven diabetic retinopathy screening solution leveraging deep learning for retinal image analysis. The system automates the detection of DR, assigns severity scores, and integrates seamlessly into the provider’s existing workflows, ensuring ease of use and immediate impact.