Artificial intelligence and deep learning in ophthalmology - present and future (Review)
- Andreea Dana Moraru
- Danut Costin
- Radu Lucian Moraru
- Daniel Constantin Branisteanu
Affiliations: Department of Ophthalmology, ‘Grigore T. Popa’ University of Medicine and Pharmacy, 700115 Iași, Romania, Department of Otorhinolaryngology, Transmed Expert, 700011 Iași; 4‘Retina Center’ Eye Clinic, 700126 Iași, Romania
- Published online on: August 12, 2020 https://doi.org/10.3892/etm.2020.9118
Copyright: © Moraru
et al. This is an open access article distributed under the
terms of Creative
Commons Attribution License.
Views: 0 (Spandidos Publications: | PMC Statistics: )
Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )
This article is mentioned in:
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.