Student Portal Britannica is the ultimate student resource for key school subjects like history, government, literature, and more.This Time in History In these videos, find out what happened this month (or any month!) in history.#WTFact Videos In #WTFact Britannica shares some of the most bizarre facts we can find.Demystified Videos In Demystified, Britannica has all the answers to your burning questions.Britannica Classics Check out these retro videos from Encyclopedia Britannica’s archives.Britannica Explains In these videos, Britannica explains a variety of topics and answers frequently asked questions.Finally, Leena requested that those who try the app leave suggestions and feedback for future improvements and updates. In the LinkedIn post, Leena also created a 57-second video demonstrating her app’s capabilities, UI, and how it reaches its results. As for the app, those who are interested in using it will need an iPhone 10, or above, with an iOS16+. 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.Ĭurrently, the app is under review within the Apple Appstore and Leena Rafeeq hopes that her app will be listed soon. 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.” Conditions and diseases the app can identify include Arcus, Melanoma, Pterygium, and Cataracts.ĭeveloped natively with SwiftUI, Leena Rafeeq says that Ogler Eyescan took six months of both research and development to get it online. Once the app completes the scan of the user’s eyes, it then goes on to use training models to diagnose. The app can also identify any light bust issues if the eyes are positioned in the scanner frame. This includes light, color, intensity, distance, and look-up points to locate the eyes within the frame range.
The way it works is that the program uses both machine learning algorithms and advanced computer vision to analyze various parameters. This is all tied to how iPhones are able to utilize specific scanning methods. According to her post on LinkedIn, the AI-powered app, Ogler Eyescan, can detect 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.
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