AI深度学习在年龄相关性黄斑变性辅助诊断中的应用

Application of deep learning artificial intelligence in the auxiliary diagnosis of age-related macular degeneration

自从人工智能(AI)技术出现后,其在各个领域被越来越多地应用并得到了快速的发展。在医学领域中,借助AI技术可自动提取图像特征并完成特征学习和分类的性能。在眼底病领域,AI可通过分析和识别眼底的照相和光学相干断层扫描从而对年龄相关性黄斑变性做出诊断,准确率可跟眼科专家相似。在未来AI可辅助医生对年龄相关性黄斑变性做出诊断,帮助基础医院进行筛查,在疾病的早期遏制其进展。但此技术存在模型识别性能不确定、运算过程不透明、需要的临床数据量过大等问题仍不能被广泛应用于临床。近年来国内在AI深度学习技术应用于眼科疾病辅助诊断方面进行了大量的研究,结果显示AI结合影像分析眼科疾病具有客观性、高效性和准确性等特点。本文针对深度学习在年龄相关性黄斑变性的辅助诊断中的研究进行综述,分析其应用进展和存在的局限性,为AI在此病的进一步应用及推广提供更多信息。

Since the advent of artificial intelligence(AI),it has been increasingly applied and rapidly developed in various fields.In the field of medicine,image features can be automatically extracted and the performance of feature learning and classification can be completed with the help of AI.In the field of ocular fundus disease,AI can give a diagnosis of age-related maculopathy by analyzing and identifying fundus photography and optical coherence tomography with an accuracy rate similar to that of ophthalmologists.In the future,AI may assist physicians in making a diagnosis of age-related macular degeneration,aid basic hospital in screening and curb its progression in the early stage of the disease.However,the technique has problems such as uncertain model recognition performance,opaque operation process,and excessive amount of clinical data required,which still cannot be widely used in the clinic.In recent years,a lot of research has been done in China in the application of deep learning with AI to assist diagnosis of ophthalmic diseases,and the results show that AI combined with imaging analysis of ophthalmic diseases has such characteristics as objectivity,efficiency and accuracy.In this article,studies on deep learning in the auxiliary diagnosis of age-related maculopathy are reviewed,and the progress on its application and the limitations that exist are analyzed,so as to provide more information on the use and extension of AI in this disease.