01928nas a2200181   4500000000100000008004100001260003000042100001400072700001300086700001400099700001300113700001200126245008800138856026000226300000800486520123800494022001401732       2023                            d  bGRENZE Scientific Society1 aRanjan N.1 aHaral R.1 aShejul A.1 aHarne K.1 aBhat S.00aDetection of Cataract and its Level based on Deep Learning using Mobile Application  uhttps://www.researchgate.net/profile/Nihar-Ranjan-11/publication/369140602_Detection_of_Cataract_and_its_Level_based_on_Deep_Learning_using_Mobile_Application/links/640b4d07a1b72772e4eb0152/Detection-of-Cataract-and-its-Level-based-on-Deep-Learning-using-  a1-73 a<p>The human eye has a natural lens that refracts the incoming light rays to help us see objects. Cataracts could be the reason why the eye's natural lens becomes cloudy. When proteins in the lens start breaking down, causing cataracts, objects may appear cloudy, fuzzy, or even less colorful. If Cataract is not identified and treated in the early stages, it could lead to complete blindness of the eye. It is mainly observed in older age groups than the younger age group, however, there are cases witnessed even in young people. We are creating a mobile application using AI and deep learning that can detect the existence of cataracts to help with the scarcity of ophthalmologists. With this application, patients can use their smartphones to click the photograph of a patient's eye and feed the data into this AI-based system that is developed using deep learning technologies. The model then determines whether the eye has a nuclear sclerotic, cortical, or posterior subcapsular. The effect of this system will result in far improvement in the delivery of public services, diagnosis and treatment, prioritization of patients, and ultimately, the prevention of blindness. This system will demonstrate encouraging outcomes.</p>
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