The Development of Optics in Modern Technology (Nano-Artificial Intelligence) In the Treatment and Early Detection of Diabetic Retinopathy in Saudi Arabia

Abstract

Diabetic retinopathy (DR) remains a leading cause of preventable blindness, yet limitations in current screening methods and treatment strategies hinder timely diagnosis and effective management. Existing studies in Saudi Arabia have largely focused on conventional diagnostic and therapeutic approaches, with insufficient integration of advanced optical artificial intelligence (AI) systems and nanotechnology-based interventions. This study aimed to evaluate the role of optics-driven AI in the early detection of DR and to investigate the efficacy of nanocarrier-assisted therapy for retinal protection. A diagnostic cohort of 500 patients underwent retinal imaging analyzed by AI and human graders against ETDRS reference standards, followed by logistic regression to identify predictors of referable DR. In a randomized pilot trial, 60 patients were assigned to nanocarrier or standard therapy arms and monitored for changes in central subfield thickness (CST) and best-corrected visual acuity (BCVA) over six months. The AI system achieved higher sensitivity than human graders (96.6% vs. 81.8%, p < 0.001) with an AUC of 0.997. Elevated HbA1c (OR = 1.41, p < 0.001) and diabetes duration (OR = 1.05, p = 0.003) were significant predictors of referable DR. Nanocarrier therapy achieved greater CST reduction (–18.7 µm, p = 0.028) and BCVA improvement (+2.6 letters, p = 0.041) without additional safety risks. These findings demonstrate the value of integrating AI-based screening with innovative nanotechnology to enhance early detection and treatment of DR.