Charfasson Sadar

Eye disease affects billions worldwide, causing vision problems that impact daily life and productivity. This research focuses on eye health in coastal Bangladesh, a region with high poverty, limited healthcare access, and environmental risks that increase eye disease prevalence. The study evaluates a community-based eye screening program using Artificial Intelligence AI to detect conditions like diabetic retinopathy, glaucoma, cataracts, and age-related macular degeneration, aiming to improve early diagnosis and care in underserved areas. The program offers a twelve-step eye screening process supported by AI-assisted fundus imaging, combined with partnerships among local organizations and healthcare providers. Screening includes community outreach, vision tests, blood pressure and glucose checks, optometrist evaluations, and selective AI imaging for higher-risk individuals based on age, diabetes, hypertension, or symptoms. Patients diagnosed with severe cataracts are offered surgery through local or regional services. The approach integrates data collection, AI analysis, clinical examinations, counseling, and referrals to support comprehensive eye care. Participants aged 35 and older from the Char Fasson sub-district undergo screening and follow-up over several months. The study collects demographic, clinical, and imaging data securely, with informed consent for storing fundus images. Researchers monitor the number of individuals screened and the prevalence of eye diseases. Safety and data privacy are maintained using encrypted systems and compliance with ethical standards. The programs feasibility, cost, and effectiveness in improving eye care accessibility are assessed throughout the study.