Moraru Andreea Dana, Costin Danut, Moraru Radu Lucian, Branisteanu Daniel Constantin
Department of Ophthalmology, 'Grigore T. Popa' University of Medicine and Pharmacy, 700115 Iaşi, Romania.
Department of Ophthalmology, 'N. Oblu' Clinical Hospital, 700309 Iași, Romania.
Exp Ther Med. 2020 Oct;20(4):3469-3473. doi: 10.3892/etm.2020.9118. Epub 2020 Aug 12.
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.
自1959年人工智能技术问世以来,它发展迅速,为科研、工业和医学带来了诸多益处。深度学习作为人工智能(AI)的一个过程,被应用于眼科的数据分析、分割、自动诊断以及可能的结果预测。深度学习与光学相干断层扫描(OCT)技术的结合已被证明在检测视网膜疾病和提高眼后段疾病的诊断性能方面是可靠的。本综述探讨了在视网膜疾病诊断中应用和使用人工智能的可能性。通过分析最新的文献数据,研究了人工智能在视网膜疾病医疗管理领域的益处和局限性。此外,还分析了人工智能参与眼科领域的未来趋势,因为人工智能将成为科学研究、诊断和治疗管理决策的一部分。