Ocular Abnormality Prevention System Using Machine learning

This research paper addresses the global concern of ocular abnormalities and the limited access to specialized eye care facilities, introducing an innovative method known as "Ocular Abnormality Prevention using Machine Learning."This approach harnesses the capabilities of artificial intelligence and machine learning to create a user-friendly at-home device system, often in the form of a mobile application, enabling individuals without easy access to eye clinics to actively monitor and manage their eye health.At its core, this research relies on state-of-the-art image recognition technology integrated seamlessly into daily life.By capturing eye images, the system can identify subtle signs of ocular abnormalities, spanning common refractive issues to more serious conditions.Continuous analysis by machine learning algorithms offers real-time feedback on eye health, along with personalized recommendations for preventive measures and early interventions to promote long-term ocular well-being.