Available online www.ejaet.com European Journal of Advances in Engineering and Technology, 2024, 11(3):45-53 Research Article ISSN: 2394 - 658X 45 Instantaneous Classification and Localization of Eye Diseases via Artificial Intelligence Joyeshree Biswas 1 , S M Mustaquim 2* , S.M. Saokat Hossain 3 , Iqtiar Md Siddique 4 1 Department of Industrial and System Engineering, The University of Oklahoma, 660 Parrington Oval, Norman, OK 73019-0390, US. 2* Department of Mathematical Science, University of Texas at El Paso, US. 3 Department of CSE Jahangirnagar University Savar 1342, Bangladesh 4 Department of Industrial, Manufacturing & Systems Engineering, University of Texas at El Paso, US. *mustaq.fcb@gmail.com _________________________________________________________________________________________ ABSTRACT The primary causes of vision impairment worldwide include glaucoma, cataract, and retinal diseases. The increasing occurrence of these disorders requires a prompt and precise diagnosis. The proposed method aims to facilitate the diagnosis of glaucoma, retinal diseases, cataracts, and other conditions for individuals. Eye disorders are classified and localized through the utilization of convolutional neural networks and artificial neural networks. The proposed method aims to decrease the incidence of acquired blindness by allowing patients to access essential care for the specified diseases in the first stages. As well as assessing the prognosis of glaucoma and retinal diseases, the adopted methodology evaluates the efficacy and safety of cataract surgery in patients with age-related macular degeneration. This study exhibits the accuracy of algorithms by analyzing fundus images from eyes with glaucoma, healthy eyes, retina issues, and cataracts. Presently, the notion of classifying photographs according to their foundation and extracting characteristics is widely acknowledged, and it also serves an essential function in the final analysis. Key words: Machine Learning, Imaging, Artificial Intelligence, Diagnosis. __________________________________________________________________________________ INTRODUCTION The advent of artificial intelligence (AI) has revolutionized medical diagnostics, and in the realm of ophthalmology, its impact is transformative. This study focuses on the real-time classification and localization of eye diseases, leveraging advanced AI algorithms. The intricate interplay of AI technologies enables swift and accurate identification of various ocular conditions, empowering healthcare professionals with timely insights for effective treatment. By amalgamating cutting-edge machine learning techniques, particularly Convolutional Neural Networks (CNNs), this research pioneers a paradigm shift in the field of ophthalmic diagnostics. The immediacy and precision offered by the AI-driven system provides an unprecedented advantage in early disease detection and localization. As we delve into the nuances of this groundbreaking approach, we unravel the potential to reshape the landscape of eye healthcare, offering rapid and reliable diagnoses that can significantly improve patient outcomes and contribute to the broader advancement of medical technology. The fast-paced developments in machine learning (ML) and artificial intelligence (AI) are leading to a significant shift in the healthcare sector (Lo et al., 2021) [1]. Identifying and pinpointing ocular disorders in real-time is a groundbreaking development among the numerous exciting applications of AI in the healthcare field (Harika et al., 2022) [20]. Undiagnosed or untreated eye conditions can lead to significant vision loss or complete loss of