Research progress in artificial intelligence assisted diabetic retinopathy diagnosis
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Xing-Zhen Fei. Department of Endocrinology, First People's Hospital of Huzhou, Huzhou University, Huzhou 313000, Zhejiang Province, China. fxz55998@163.com; Zhen-Tao Zhu. Department of Ophthalmology, Huai'an Hospital of Huai'an City, Huai'an 223000, Anhui Province, China. jshayyzzt@163.com

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Supported by Huzhou Science and Technology Planning Program (No.2019GY13).

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    Abstract:

    Diabetic retinopathy (DR) is one of the most common retinal vascular diseases and one of the main causes of blindness worldwide. Early detection and treatment can effectively delay vision decline and even blindness in patients with DR. In recent years, artificial intelligence (AI) models constructed by machine learning and deep learning (DL) algorithms have been widely used in ophthalmology research, especially in diagnosing and treating ophthalmic diseases, particularly DR. Regarding DR, AI has mainly been used in its diagnosis, grading, and lesion recognition and segmentation, and good research and application results have been achieved. This study summarizes the research progress in AI models based on machine learning and DL algorithms for DR diagnosis and discusses some limitations and challenges in AI research.

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Yun-Fang Liu, Yu-Ke Ji, Fang-Qin Fei, et al. Research progress in artificial intelligence assisted diabetic retinopathy diagnosis. Int J Ophthalmol, 2023,16(9):1395-1405

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Publication History
  • Received:April 28,2023
  • Revised:June 14,2023
  • Adopted:
  • Online: August 22,2023
  • Published: