Open AccessArtificial intelligence and deep learning in ophthalmology - present and future (Review)
Author(s) -
Andreea Moraru,
D Costin,
Radu Lucian Moraru,
Dumitru Brănișteanu
Publication year - 2020
Publication title -
experimental and therapeutic medicine
Language(s) - English
Resource type - Journals
eISSN - 1792-1015
pISSN - 1792-0981
DOI - 10.3892/etm.2020.9118
Subject(s) - deep learning , artificial intelligence , optical coherence tomography , computer science , process (computing) , data science , medicine , optometry , ophthalmology , operating system
Since its introduction in 1959, artificial intelligence technology has evolved rapidly and helped benefit research, industries and medicine. Deep learning, as a process of artificial intelligence (AI) is used in ophthalmology for data analysis, segmentation, automated diagnosis and possible outcome predictions. The association of deep learning and optical coherence tomography (OCT) technologies has proven reliable for the detection of retinal diseases and improving the diagnostic performance of the eye's posterior segment diseases. This review explored the possibility of implementing and using AI in establishing the diagnosis of retinal disorders. The benefits and limitations of AI in the field of retinal disease medical management were investigated by analyzing the most recent literature data. Furthermore, the future trends of AI involvement in ophthalmology were analyzed, as AI will be part of the decision-making regarding the scientific investigation, diagnosis and therapeutic management.