Mobile Application for Cataract and Conjunctivitis Detection

Abstract

This study introduces a cutting-edge mobile application that will revolutionize eye care. The program focuses on the detection and remote monitoring of cataracts and conjunctivitis by utilizing the capabilities of cell phones. Precise diagnostics are made possible by combining artificial intelligence, machine learning, and digital imagery. The possibilities, difficulties, and prospects of mobile-based eye problem detection are examined through a comprehensive literature analysis. The methodology, which includes image processing and deep learning methods for cataract and conjunctivitis identification, is described in depth in the publication. The app also includes a chatbot for user engagement and for users to acknowledge further needed information. The application also facilitates a channeling service and a treatment reminder service. The advantages of mobile-based detection, privacy issues, user-centered design, and the part played by international health organizations in technology adoption are all examined in the conversation. The conclusion highlights the application's transformational potential and urges continuous cooperation between medical experts, technologists, and policymakers.