Optivue - A Smart Approach To Eye Health Screening

The increasing prevalence of refractive eye conditions such as myopia, hypermetropia, and presbyopia highlights the need for early detection and intervention to prevent vision impairment. This paper presents the development of an AI-powered application that utilizes machine learning (ML) techniques to detect and classify common eye conditions in real-time. The proposed system is trained using a dataset of annotated eye images, allowing it to analyze new images captured and provide instant diagnostic results. The model leverages convolutional neural networks (CNN) and transformer-based architectures to enhance accuracy and robustness in detecting refractive errors. Advanced image preprocessing techniques, including contrast enhancement and noise reduction, ensure reliable input quality for the AI model. The application is designed to provide user-friendly, real-time feedback on whether the captured image indicates a potential eye condition or normal vision. Experimental evaluations demonstrate the model’s high accuracy, sensitivity, and specificity in detecting refractive errors. This innovative solution aims to assist ophthalmologists and healthcare providers in offering early diagnosis and personalized treatment recommendations. Future work will focus on expanding the dataset and integrating additional eye conditions for comprehensive diagnostic capabilities.