Application of Artificial Intelligence in Ophthalmology for the Diagnosis and Treatment of Eye Diseases

In this paper, we present the main aspects of artificial intelligence application in ophthalmology for the diagnosis and treatment of eye diseases on the example of developing a computer system for personalizing retinal laser photocoagulation. Approaches to the automation of eye disease prediction and treatment based on fundus images are described. Four problems of applying the neural network approach are highlighted. Decision support information technology for personalizing laser treatment of diabetic macular edema and identifying prognostic factors of surgical outcome using methods of intellectual analysis of large unstructured data is described. The system allows the doctor to form a plan of optimal coagulation arrangement for retinal laser coagulation for each case, to predict the quality of laser coagulation depending on the initial data on the localization and severity of edema and to improve his skills by comparing the result of coagulation performed and the coagulation plan proposed by the system.