Title: A proposed accurate system for diagnosing low vision
Authors: Mohammed Mostafa Qunoo, Samy S. Abu-Naser
Volume: 9
Issue: 6
Pages: 23-32
Publication Date: 2025/06/28
Abstract:
Low vision is a significant global health issue that affects millions of individuals, limiting their daily activities and reducing their quality of life. Accurate and early diagnosis is essential for effective management and treatment, yet existing diagnostic methods often fall short due to various limitations in precision and accessibility. This paper proposes an innovative and accurate system for diagnosing low vision, leveraging advanced technologies such as artificial intelligence and expert systems.The proposed system integrates patient history, vision test results, and imaging data to provide precise diagnoses and tailored recommendations. Designed with a user-friendly interface, the system is intended to assist ophthalmologists, optometrists, and general practitioners in diagnosing a wide range of low vision conditions efficiently. Initial evaluations suggest the system's potential to significantly enhance diagnostic accuracy and patient outcomes, while also reducing the burden on healthcare professionals. This work represents a step forward in bridging the gap between technology and accessible eye care for patients worldwide.