Investigate a Diagnosis of Eye Diseases using Imaging Ophthalmic Data

The utilization of computers in any field by using deep learning (DL) allows task performance with high efficiency and least human errors (1-2). This is possible as most of the tasks are completed by robotic computers with minimal participation of humans. Moreover, artificial intelligence has been one of the most influential information technology revolutions in health science as these robotic operations have immense importance and application in medicine science. Further, the application of artificial intelligence in ophthalmology mainly focused on the diseases like diabetic retinopathy, age-related macular degeneration, glaucoma, retinopathy of prematurity, age-related or congenital cataract and few with retinal vein occlusion. Artificial intelligence mainly uses machine learning or DL that has ability to process input data without the need for manual feature engineering. In this way, completely automated systems recognise the intricate structures in high-dimensional data through projection onto a lower dimensional manifold. So, AI allows higher accuracies in many domains, including natural language processing, computer vision and voice recognition in comparison to conventional techniques. The present study is focused to evaluate potential of artificial intelligence (AI) in ophthalmology by concentrating of important ophthalmological diseases. Citation: Dr. Kurikkil Veettil Yooseff Ibrahim. "Investigate a Diagnosis of Eye Diseases using Imaging Ophthalmic Data." Global Research and Development Journal For Engineering 4.11 (2019): 8 - 17.