11-Year-Old Develops New AI-Powered App That Detects Eye Diseases With Up to 70% Accuracy
An 11-year-old programming prodigy named Leena Rafeeq announced the creation of a new AI app that can detect eye diseases. According to her post on LinkedIn, the AI-powered app, Ogler Eyescan, can detect diseases with up to 70% accuracy. This is all tied to how iPhones are able to utilize specific scanning methods. The way it works is that the program uses both machine learning algorithms and advanced computer vision to analyze various parameters.
This includes light, color, intensity, distance, and look-up points to locate the eyes within the frame range. The app can also identify any light bust issues if the eyes are positioned in the scanner frame. Once the app completes the scan of the user’s eyes, it then goes on to use training models to diagnose. Conditions and diseases the app can identify include Arcus, Melanoma, Pterygium, and Cataracts.
Developed natively with SwiftUI, Leena Rafeeq says that Ogler Eyescan took six months of both research and development to get it online. During that time, she educated herself about different conditions/diseases that can affect the eye as well as, “computer vision, algorithms, machine learning models, and advanced levels of Apple iOS development, including sensors data, AR, CreateML, CoreML, and more.”
If proven to be able to detect conditions and diseases that affect the eye at over 70%, it could be a new way to help those who have access to smartphones but not certain healthcare infrastructure to scan for issues themselves, and then reach out for help early in a disease’s progression to make treatment more affordable.
Currently, the app is under review within the Apple Appstore and Leena Rafeeq hopes that her app will be listed soon. As for the app, those who are interested in using it will need an iPhone 10, or above, with an iOS16+. In the LinkedIn post, Leena also created a 57-second video demonstrating her app’s capabilities, UI, and how it reaches its results. Finally, Leena requested that those who try the app leave suggestions and feedback for future improvements and updates.
Originally posted on OpenDataScience.com
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