Chief & Presenting Author: Dr.Dinesh Verma

Abstract

Back ground: Eye care accessibility remains a significant challenge in rural India, where limited resources and infrastructure impede regular screening and diagnosis.
Study Design: Artificial Intelligence (AI) driven low-touch, low-cost augmented/virtual reality (AR/VR)-based portable diagnostic device SEEMOS was used to screen eye disorders in a rural population in South Goa.
Purpose: Cost-effectiveness of using SEEMOS devices leveraging the ubiquity of primary healthcare workers to conduct preliminary eye screenings.
Methods: One hundred volunteers were screened using the SEEMOS device in a randomised controlled trial for detection and grading of diabetic retinopathy was compared with Ophthalmologist. Cost-effective analysis was done.
Results: there was 91% concurrence in the results obtained by ASHA-level workers with ophthalmologists.
Conclusion: Mass screening of diabetic retinopathy by ASHA workers using portable devices with AI is cost-effective.