ISSN :3049-2335
Ammar Almutawa, Mustafa Kafyyah, Hashim Alattas and Mohammed Mubarak
Adv. Knowl. Based Syst. Data Sci. Cybersecur., 3 (2):579-599
Ammar Almutawa : Department of Information System and Technology, College of Computer Science and Engineering, University of Jeddah. Jeddah 21493, Saudi Arabia Saudi Arabia
Mustafa Kafyyah : Department of Information System and Technology, College of Computer Science and Engineering, University of Jeddah
Hashim Alattas : Department of Information System and Technology, College of Computer Science and Engineering, University of Jeddah
Mohammed Mubarak : Department of Information System and Technology, College of Computer Science and Engineering, University of Jeddah
DOI: https://dx.doi.org/10.54364/cybersecurityjournal.2026.3229
Article History: Received on: 03-Jul-26, Accepted on: 11-Aug-26, Published on: 28-Aug-26
Corresponding Author: Ammar Almutawa
Email: ahalmutawwa@uj.edu.sa
Citation: Ammar Almutawa, Mustafa Kafyyah, Hashim Alattas, Osama Alghamdi, Mohammed Mubarak, Ammar Yahya, (2026). Deep Learning Based Detection of Eye Conditions Using External Eye Images. Adv. Know. Base. Syst. Data Sci. Cyber., 3 (2 ):579-599
Eye conditions such as
anemia, cataract, conjunctivitis and uveitis can often be identified from an
external inspection. However, many people in remote or low resource areas lack
access to proper healthcare facilities. This project proposes a low-cost, non-invasive
system that uses external eye images to provide an initial non-diagnostic
assessment of the conditions. A smartphone user uploads a close-up image of the
eye, the system verifies that an eye is present and preprocesses the image. The
processed image is then passed through a deep learning model that estimates the
likelihood of disease presence. Data was sourced from publicly available
datasets. The prototype application’s outputs can show the likelihood of the
disease and a simple next-step guide to help the user. This would not replace
doctors, but it
could provide early guidance for people living far away from healthcare centers
and make basic screening more accessible.