Charfasson Sadar

Eye disease affects 2.2 billion people worldwide and can lead to vision loss impacting daily life, work, and social activities. This research evaluates a community-based eye screening program in coastal Bangladesh, a region with high poverty, limited healthcare access, and elevated rates of eye diseases like cataracts, diabetic retinopathy, glaucoma, and age-related macular degeneration. The study explores the use of Artificial Intelligence (AI) to assist in early detection and improve accessibility and affordability of eye care in underserved areas. The screening process involves twelve organized steps managed by electronic health records, including community awareness, participant registration, vital signs measurement, vision testing, optometrist evaluation, and informed consent for imaging. Fundus imaging with AI analysis is selectively offered to higher-risk individuals, such as those with diabetes, hypertension, age 50 or older, or optometrist recommendations. Diagnosed cataract patients with moderate to severe visual impairment are offered surgery through local or regional services. The program uses advanced AI software and collaborates with multiple partners to deliver comprehensive eye screening and follow-up care. Participants undergo evaluations including blood pressure and blood glucose tests, vision assessment, imaging, AI-assisted disease detection, ophthalmologist review, counseling, and referral as needed. Data security and patient privacy are carefully maintained. The study measures the number of individuals screened over 12 months and analyzes demographic and diagnostic data to assess feasibility, performance, equity, and cost of the screening model. The project duration is approximately 10 months with ongoing recruitment, screening, and follow-up.